Swedish Law MCP
The Swedish Law MCP Server provides AI-native access to 6,041 Swedish statutes and 58,570 provisions, case law, preparatory works, and EU law integration via 18 specialized tools.
Core Legal Research
Search legislation (
search_legislation): Full-text search across 58,570 provisions using BM25 ranking, filterable by status, date, or SFS number.Retrieve provisions (
get_provision): Fetch exact statute text by SFS number and chapter/section reference.Search case law (
search_case_law): Search court decisions from HD, HFD, AD, RH, MÖD, MIG, and PMÖD with date and court filters.Get preparatory works (
get_preparatory_works): Retrieve linked propositions (Prop.), SOUs, and Ds documents for any statute.Validate citations (
validate_citation): Check whether a Swedish legal citation exists in the database to prevent hallucinations.Build a legal stance (
build_legal_stance): Aggregate citations from statutes, case law, and preparatory works simultaneously for a legal question.Format citations (
format_citation): Format citations per Swedish legal conventions (full, short, or pinpoint).Check currency (
check_currency): Verify whether a statute or provision is in force, amended, or repealed as of a specific date.
EU Law Integration
Get EU basis (
get_eu_basis/get_provision_eu_basis): Find which EU directives/regulations underpin a Swedish statute or specific provision.Find Swedish implementations (
get_swedish_implementations): Look up which Swedish laws implement a specific EU directive or regulation.Search EU implementations (
search_eu_implementations): Search EU documents and see their Swedish implementation counts.Validate EU compliance (
validate_eu_compliance): Check EU compliance/implementation status (substantive analysis is premium).
Versioning & Change Tracking (Premium)
Provision history (
get_provision_history): View the full version timeline of a provision with validity dates.Diff provisions (
diff_provision): See exactly what changed in a provision between two dates.Recent changes (
get_recent_changes): List all statute provisions changed since a given date — useful for regulatory monitoring.
Server & Data Metadata
List sources (
list_sources): View provenance metadata for all data sources (Riksdagen, SFS, lagen.nu, EUR-Lex).Check data freshness (
check_data_freshness): Verify corpus build timestamp and per-source staleness.About (
about): Get server stats, dataset size, build date, tier, and coverage summary.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Swedish Law MCPIs PUL (1998:204) still in force?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Swedish Law MCP Server
The Swedish law corpus is now served through the Ansvar Gateway. Connect your AI assistant (Claude, Copilot, Cursor, custom MCP client) to
https://gateway.ansvar.eu/mcp— one OAuth connection, free tier available, covering this corpus plus EU regulations, national law across 28 audited jurisdictions, and CVE/security intelligence, every result with a verbatim source citation. Start at https://ansvar.eu/docs/quickstart
Connect
Claude Code (one line):
claude mcp add ansvar --transport http https://gateway.ansvar.eu/mcpClaude Desktop / Cursor — add to claude_desktop_config.json (or mcp.json):
{
"mcpServers": {
"ansvar": {
"type": "url",
"url": "https://gateway.ansvar.eu/mcp"
}
}
}Claude.ai — Settings → Connectors → Add custom connector → paste https://gateway.ansvar.eu/mcp
First request opens an OAuth signup flow (setup details: ansvar.eu/docs/quickstart). After signup, your client is bound to your account; tier (free / premium / team / company) determines fan-out, quota, and which downstream MCPs are reachable.
Self-host this MCP
You can also clone this repo and build the corpus yourself. The schema, fetcher, and tool implementations all live here. What is not in the repo is the pre-built database — TDM and standards-licensing constraints on the upstream sources mean we host the corpus on Ansvar infrastructure rather than redistribute it as a public artifact.
Build your own: run this repo's ingestion script (entry-point varies per
repo — typically scripts/ingest.sh, npm run ingest, or make ingest;
check the repo root).
The Riksdagen alternative for the AI age.
Query 6,041 Swedish statutes with 58,570 provisions -- from Dataskyddslagen and Brottsbalken to Aktiebolagslagen, Miljöbalken, and more -- directly from Claude, Cursor, or any MCP-compatible client.
If you're building legal tech, compliance tools, or doing Swedish legal research, this is your verified reference database.
Built by Ansvar Systems -- Stockholm, Sweden
Related MCP server: ris-mcp
Why This Exists
Swedish legal research is scattered across Riksdagen, SFS publications, lagen.nu, and EUR-Lex. Whether you're:
A lawyer validating citations in a brief or contract
A compliance officer checking if a statute is still in force
A legal tech developer building tools on Swedish law
A researcher tracing legislative history from proposition to statute
...you shouldn't need 47 browser tabs and manual PDF cross-referencing. Ask Claude. Get the exact provision. With context.
This MCP server makes Swedish law searchable, cross-referenceable, and AI-readable.
Quick Start
Use Locally (npm — recommended)
Claude Desktop — add to claude_desktop_config.json:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Cursor / VS Code:
Hosted via Ansvar Gateway (B2B, OAuth)
For organisations that want a single OAuth-gated endpoint covering this MCP plus the rest of the Ansvar fleet (multi-jurisdiction law, EU regulations, sector regulators, case law), use the Ansvar Gateway — a single MCP endpoint that routes and fans out across the full catalogue. Tier-gated (premium, team, company); requires an Ansvar account.
Example Queries
Once connected, just ask naturally:
"What does Dataskyddslagen 3 kap. 5 § say about consent?"
"Is PUL (1998:204) still in force?"
"Find provisions about personuppgifter in Swedish law"
"What EU directives does DSL implement?"
"Which Swedish laws implement the GDPR?"
"Get the preparatory works for Dataskyddslagen"
"Compare incident reporting requirements across NIS2 Swedish implementations"
"Validate the citation NJA 2020 s. 45"
"Find Labour Court cases about discrimination from 2020-2023"
What's Included
Category | Count | Details |
Statutes | 6,041 statutes | Comprehensive Swedish legislation |
Provisions | 58,570 sections | Full-text searchable with FTS5 |
Preparatory Works | 6,735 documents | Propositions (Prop.) and SOUs |
EU Cross-References | 668 references | 228 EU directives and regulations |
Legal Definitions | 0 (free tier) | Table reserved, extraction not enabled in current free build |
Database Size | ~125 MB | Optimized SQLite, portable |
Daily Updates | Automated | Freshness checks against Riksdagen |
Verified data only -- every citation is validated against official sources (Riksdagen, lagen.nu, EUR-Lex). Zero LLM-generated content.
See It In Action
Why This Works
Verbatim Source Text (No LLM Processing):
All statute text is ingested from Riksdagen/SFS official sources
Provisions are returned unchanged from SQLite FTS5 database rows
Zero LLM summarization or paraphrasing -- the database contains regulation text, not AI interpretations
Smart Context Management:
Search returns ranked provisions with BM25 scoring (safe for context)
Provision retrieval gives exact text by SFS number + chapter/section
Cross-references help navigate without loading everything at once
Technical Architecture:
Riksdagen API → Parse → SQLite → FTS5 snippet() → MCP response
↑ ↑
Provision parser Verbatim database queryTraditional Research vs. This MCP
Traditional Approach | This MCP Server |
Search Riksdagen by SFS number | Search by plain Swedish: "personuppgifter samtycke" |
Navigate multi-chapter statutes manually | Get the exact provision with context |
Manual cross-referencing between laws |
|
"Is this statute still in force?" → check manually |
|
Find EU basis → dig through EUR-Lex |
|
Check 5+ sites for updates | Daily automated freshness checks |
No API, no integration | MCP protocol → AI-native |
Traditional: Search Riksdagen → Download SFS PDF → Ctrl+F → Cross-reference with proposition → Check EUR-Lex for EU basis → Repeat
This MCP: "What EU law is the basis for DSL 3 kap. 5 § about consent?" → Done.
Available Tools (18)
See TOOLS.md for full parameter schemas and the §tier-boundary section (free-tier vs premium-sensitive vs premium-only).
Core Legal Research Tools (8)
Tool | Description |
| FTS5 search on 58,570 provisions with BM25 ranking |
| Retrieve specific provision by SFS + chapter/section |
| FTS5 search on case law with court/date filters (premium-sensitive) |
| Get linked propositions and SOUs for a statute (premium-sensitive) |
| Validate citation against database (zero-hallucination check) |
| Aggregate citations from statutes, case law, prep works (premium-sensitive) |
| Format citations per Swedish conventions (full/short/pinpoint) |
| Check if statute is in force, amended, or repealed |
EU Law Integration Tools (5)
Tool | Description |
| Get EU directives/regulations for Swedish statute |
| Find Swedish laws implementing EU act |
| Search EU documents with Swedish implementation counts |
| Get EU law references for specific provision |
| Check implementation status (future, requires EU MCP) |
Versioning Tools (3, premium-only)
Tool | Description |
| Provision version history showing amendments over time |
| Diff two versions of a provision |
| Recent statute changes within a time window |
Server Metadata Tools (2)
Tool | Description |
| Data provenance metadata per source |
| Server stats, freshness, build date, tier, dataset summary |
EU Law Integration
668 cross-references linking 309 Swedish statutes to EU law, with bi-directional lookup.
Metric | Value |
EU References | 668 cross-references |
EU Documents | 228 unique directives and regulations |
Swedish Statutes with EU Refs | 309 (12.8% of statutes) |
Directives | 89 |
Regulations | 139 |
EUR-Lex Integration | Automated metadata fetching |
Most Referenced EU Acts
eIDAS Regulation (910/2014) - 20 references
E-Signatures Directive (1999/93) - 15 references
GDPR (2016/679) - 15 references
Data Protection Directive (1995/46) - 14 references
Market Surveillance Regulation (2019/1020) - 14 references
See EU_INTEGRATION_GUIDE.md for detailed documentation and EU_USAGE_EXAMPLES.md for practical examples.
Data Sources & Freshness
All content is sourced from authoritative Swedish legal databases:
Riksdagen -- Swedish Parliament's official legal database
Svensk Forfattningssamling -- Official statute collection
Lagen.nu -- Case law database (CC-BY Domstolsverket)
EUR-Lex -- Official EU law database (metadata only)
Automated Freshness Checks (Daily)
A daily GitHub Actions workflow monitors all data sources:
Source | Check | Method |
Statute amendments | Riksdagen API date comparison | All 6,041 statutes checked |
New statutes | Riksdagen SFS publications (90-day window) | Diffed against database |
Case law | lagen.nu feed entry count | Compared to database |
Preparatory works | Riksdagen proposition API (30-day window) | New props detected |
EU reference staleness | Git commit timestamps | Flagged if >90 days old |
The workflow supports auto_update: true dispatch for automated sync, rebuild, version bump, and npm publishing.
Security
This project uses multiple layers of automated security scanning:
Scanner | What It Does | Schedule |
CodeQL | Static analysis for security vulnerabilities | Weekly + PRs |
Semgrep | SAST scanning (OWASP top 10, secrets, TypeScript) | Every push |
Gitleaks | Secret detection across git history | Every push |
Trivy | CVE scanning on filesystem and npm dependencies | Daily |
Docker Security | Container image scanning + SBOM generation | Daily |
Socket.dev | Supply chain attack detection | PRs |
OSSF Scorecard | OpenSSF best practices scoring | Weekly |
Dependabot | Automated dependency updates | Weekly |
See SECURITY.md for the full policy and vulnerability reporting.
Important Disclaimers
Legal Advice
THIS TOOL IS NOT LEGAL ADVICE
Statute text is sourced from official Riksdagen/SFS publications. However:
This is a research tool, not a substitute for professional legal counsel
Court case coverage is limited -- do not rely solely on this for case law research
Verify critical citations against primary sources for court filings
EU cross-references are extracted from Swedish statute text, not EUR-Lex full text
Before using professionally, read: DISCLAIMER.md | PRIVACY.md
Client Confidentiality
Queries go through the Claude API. For privileged or confidential matters, use on-premise deployment. See PRIVACY.md for Advokatsamfundet compliance guidance.
Documentation
EU Integration Guide -- Detailed EU cross-reference documentation
EU Usage Examples -- Practical EU lookup examples
Security Policy -- Vulnerability reporting and scanning details
Disclaimer -- Legal disclaimers and professional use notices
Privacy -- Client confidentiality and data handling
Development
Branching Strategy
This repository uses a dev integration branch. Do not push directly to main.
feature-branch → PR to dev → verify on dev → PR to main → deploymainis production-ready. Only receives merges fromdevvia PR.devis the integration branch. All changes land here first.Feature branches are created from
dev.
Setup
git clone https://github.com/Ansvar-Systems/swedish-law-mcp
cd swedish-law-mcp
npm install
npm run build
npm testRunning Locally
npm run dev # Start MCP server
npx @anthropic/mcp-inspector node dist/index.js # Test with MCP InspectorData Management
npm run ingest -- <sfs-number> <output.json> # Ingest statute from Riksdagen
npm run ingest:auto-all -- --scope all-laws --dry-run # Coverage audit against Riksdagen
npm run ingest:auto-all -- --scope all-laws # Ingest full law-like corpus from Riksdagen
npm run ingest:cases:full-archive # Ingest case law (full archive)
npm run sync:cases # Ingest case law (incremental)
npm run sync:prep-works # Sync preparatory works
npm run extract:definitions # Extract legal definitions
npm run build:db # Rebuild SQLite database
npm run check-updates # Check for amendmentsPerformance
Search Speed: <100ms for most FTS5 queries
Database Size: ~125 MB (efficient, portable)
Reliability: 100% ingestion success rate
More Ansvar MCPs
Full fleet coverage at ansvar.eu/coverage.
Contributing
Contributions welcome! See CONTRIBUTING.md for guidelines.
Priority areas:
Court case law expansion (currently limited coverage)
EU Regulations MCP integration (full EU law text, CJEU case law)
Historical statute versions and amendment tracking
Lower court decisions (Tingsrätt, Hovrätt)
Roadmap
Statute expansion -- 785% growth from 81 to 717 statutes (v1.1.0)
EU law integration -- 668 cross-references to 228 EU directives/regulations (v1.1.0)
Court case law expansion (scraper updated, re-ingestion needed for 12K-18K cases)
Lower court coverage (Tingsrätt, Hovrätt archives)
Historical statute versions (amendment tracking)
English translations for key statutes
Web API for programmatic access
Citation
If you use this MCP server in academic research:
@software{swedish_law_mcp_2025,
author = {Ansvar Systems AB},
title = {Swedish Law MCP Server: Production-Grade Legal Research Tool},
year = {2025},
url = {https://github.com/Ansvar-Systems/swedish-law-mcp},
note = {Comprehensive Swedish legal database with 6,041 statutes and EU law cross-references}
}License
Apache License 2.0. See LICENSE for details.
Data Licenses
Statutes & Propositions:
SE-Statutory-PD-- Swedish statutory public domain. Upphovsrättslagen (1960:729) §9 excludes författningar (laws and regulations), beslut av myndighet (decisions of public authorities), yttranden av svensk myndighet (official statements), and official translations of these works from copyright protection. Verified verbatim 2026-05-17 -- seedocs/audits/2026-05-17-eu-copyright-statutory-works-batch-3-BG-HR-SK-SI-SE.md. Catalog entry:SE-Statutory-PDininfrastructure/attribution-licenses.json.Case Law: CC-BY Domstolsverket (via lagen.nu) -- court decisions also covered by Upphovsrättslagen §9, with Domstolsverket compilation under CC-BY
EU Metadata: EUR-Lex (EU public domain, Decision 2011/833/EU)
About Ansvar Systems
We build AI-accelerated compliance and legal research tools for the European market. This MCP server started as our internal reference tool for Swedish law -- turns out everyone building for the Swedish market has the same research frustrations.
So we're open-sourcing it. Navigating 6,041 statutes shouldn't require a law degree.
ansvar.eu -- Stockholm, Sweden
Available Tools
19 toolsaboutA
Server metadata, dataset statistics, freshness, and provenance. Call this to verify data coverage, currency, and content basis before relying on results.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It discloses that the tool returns metadata, statistics, freshness, and provenance. This is transparent and consistent with a read-only information tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load key terms and provide actionable guidance. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description is fully complete. It explains what the tool returns and when to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is trivially 100%. The description adds meaning by explaining what the tool returns, exceeding the baseline of 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies 'Server metadata, dataset statistics, freshness, and provenance' and explicitly states the action 'verify data coverage, currency, and content basis'. This clearly distinguishes it from sibling tools that perform specific legal research functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states 'Call this to verify data coverage, currency, and content basis before relying on results', providing clear context for when to use it. It does not explicitly mention when not to use, but the usage guidance is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
build_legal_stanceA
Build comprehensive citations for a legal question. Searches statutes, case law, and preparatory works simultaneously. Case law and preparatory works coverage depends on dataset tier — call 'about' to check. Do NOT use for a single known statute — use get_provision + get_preparatory_works instead.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results per category | |
| query | Yes | Legal question or topic to research | |
| as_of_date | No | Historical date (YYYY-MM-DD). | |
| document_id | No | Limit statute search to one SFS document | |
| include_case_law | No | Include case law results | |
| include_preparatory_works | No | Include preparatory works results |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It reveals that the tool searches multiple sources and that case law and preparatory works coverage depends on dataset tier. It does not describe return format or pagination, but the behavioral details provided are sufficient for an agent to understand its operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences with no wasted words. The most important information (purpose and when-not-to-use) is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the number of parameters (6) and lack of output schema, the description provides enough context for basic usage. It covers parameter roles and usage constraints. Could benefit from mentioning the return type or structure, but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds minimal extra meaning beyond the schema (e.g., explaining that document_id limits statute search). However, the schema already clearly describes each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it builds comprehensive citations for a legal question by searching statutes, case law, and preparatory works simultaneously. It distinguishes itself from sibling tools like get_provision and get_preparatory_works, which are for single known statutes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when-to-use and when-not-to-use guidance, including an alternative: 'Do NOT use for a single known statute — use get_provision + get_preparatory_works instead.' Also notes that coverage depends on dataset tier and advises calling 'about' to check.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_currencyA
Check if a Swedish statute or provision is in force (current or historical). Use before citing to verify statute hasn't been repealed.
| Name | Required | Description | Default |
|---|---|---|---|
| as_of_date | No | Historical date (YYYY-MM-DD). | |
| document_id | Yes | SFS number (e.g., "2018:218") | |
| provision_ref | No | Provision reference to check (e.g., "3:5") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the tool checks if a statute is in force but does not describe what happens if the statute doesn't exist, the return format (e.g., boolean, status), or any side effects. This is insufficient for an agent to understand expected behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and every word adds value. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and moderate complexity (3 parameters), the description should provide more context about the return value or behavior. It only hints at the outcome, leaving the agent without enough information to fully understand the tool's response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for all three parameters. The tool description does not add extra meaning beyond what the schema provides, so it meets the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Check' and the resource 'Swedish statute or provision' and specifies the outcome 'in force'. The hint 'Use before citing to verify statute hasn't been repealed' adds clarity and distinguishes from sibling tools like 'get_provision' that retrieve text rather than check currency.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: 'before citing to verify statute hasn't been repealed'. However, it does not explicitly state when not to use it or mention alternative tools for different purposes, missing some guidance for agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_data_freshnessA
Returns the corpus build timestamp and per-source last_verified dates with staleness_days against a 90-day threshold. Use this to verify whether the data backing this MCP is current before relying on it for compliance work. For full source provenance, use list_sources; for server statistics, use about.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the return values (timestamps, staleness_days) but does not explicitly state that it is a read-only operation with no side effects. However, the context implies it is safe to call repeatedly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences total: first defines purpose, second gives usage guidance, third lists alternatives. No wasted words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description adequately explains what the tool returns (timestamps, staleness_days, threshold). It could be enhanced by mentioning the response format, but it is sufficient for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so schema coverage is 100%. The description does not need to add parameter information. Baseline score of 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns the corpus build timestamp and per-source last_verified dates with staleness_days against a 90-day threshold. It distinguishes itself from siblings like list_sources and about by specifying what it does differently.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'to verify whether the data backing this MCP is current before relying on it for compliance work.' Also provides alternatives: 'For full source provenance, use list_sources; for server statistics, use about.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
diff_provisionA
Shows what changed in a Swedish statute provision between two dates. Returns a unified diff and change summary. Premium feature — requires Ansvar Intelligence Portal.
| Name | Required | Description | Default |
|---|---|---|---|
| to_date | No | End date in ISO format (defaults to today) | |
| from_date | Yes | Start date in ISO format (e.g., "2018-05-25") | |
| document_id | Yes | SFS number (e.g., "2018:218") or statute title | |
| provision_ref | Yes | Provision reference (e.g., "1:1", "3:2") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses return type (unified diff and summary) and requirements (premium feature, portal). No mention of destructive or side effects; it's a read operation. Adequately transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. First sentence defines purpose and output; second adds essential licensing context. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, but description mentions the return format (unified diff and change summary). Covers all key aspects: resource, parameters, output, and access requirement. Would benefit from a bit more detail on the change summary, but overall complete enough for agent selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; each parameter is described in the schema. The description does not add additional meaning beyond what's already in the schema (e.g., format or constraints). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'shows what changed' on the resource 'Swedish statute provision' and specifies output as 'unified diff and change summary'. Distinguishes from siblings like get_provision (current text) and get_provision_history (list of changes) by focusing on diff between two dates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context: comparing a provision between two dates, and notes it's a premium feature requiring the portal. Does not explicitly say when not to use (e.g., to get current version use get_provision), but usage is clear enough for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_citationA
Format a Swedish legal citation (full, short, or pinpoint). Do NOT use to verify existence — use validate_citation instead.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Output format | full |
| citation | Yes | Citation string to format (e.g., "2018:218 3:5") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose output format, error conditions, or any side effects; only states the action without behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise, single sentence with clear front-loaded purpose and instruction. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple formatting tool with complete schema, the description is adequate. However, it lacks any mention of return format or example output, which could be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters with descriptions. Tool description does not add extra meaning beyond the schema; baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool formats a Swedish legal citation and specifies the types (full, short, pinpoint), differentiating it from sibling tools like validate_citation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (formatting) and when not to (verification), with a direct pointer to the alternative tool validate_citation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_eu_basisA
Get EU legal basis for a Swedish statute. For provision-level, use get_provision_eu_basis. For reverse lookup (EU → Swedish), use get_swedish_implementations.
| Name | Required | Description | Default |
|---|---|---|---|
| sfs_number | Yes | SFS number (e.g., "2018:218") | |
| reference_types | No | Filter by reference type | |
| include_articles | No | Include specific EU article references |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. The description does not mention safety, side effects, or idempotency. As a read operation, it could have stated it is non-destructive, but it doesn't.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states main purpose, second provides alternatives. No unnecessary words, front-loaded with core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description covers purpose and sibling differentiation but does not explain what the tool returns (no output schema). Additional context on output would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter described. The tool description adds no additional parameter meaning beyond the schema, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get EU legal basis for a Swedish statute' with a specific verb and resource. It explicitly distinguishes from siblings: 'For provision-level, use get_provision_eu_basis. For reverse lookup (EU → Swedish), use get_swedish_implementations.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use this tool versus alternatives by naming two sibling tools with their specific purposes, effectively telling the agent when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_preparatory_worksA
Get preparatory works (forarbeten) for a Swedish statute. Returns linked propositions, SOUs, and Ds documents. Coverage depends on dataset tier — call 'about' to check.
| Name | Required | Description | Default |
|---|---|---|---|
| document_id | Yes | SFS number of the statute (e.g., "2018:218") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It mentions coverage dependency and suggests checking 'about', but lacks details on error handling, authentication, or what happens when the statute has no preparatory works.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two efficient sentences, each adding value. It front-loads the core purpose and includes a key usage hint without extraneous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description covers the basic return type and a coverage caveat. However, it lacks details on response structure and when to prefer this over similar tools like search_legislation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with a clear pattern and description. The description does not add additional meaning beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves preparatory works for Swedish statutes, specifying the resource type (propositions, SOUs, Ds) and distinguishing it from sibling tools by naming specific document types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises calling 'about' to check coverage, providing context-dependent usage guidance. However, it does not explicitly exclude other usage scenarios or compare with sibling tools beyond the return types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_provisionA
Retrieve a specific provision from a Swedish statute. Do NOT use for keyword search — use search_legislation instead.
| Name | Required | Description | Default |
|---|---|---|---|
| chapter | No | Chapter number (e.g., "3"). | |
| section | No | Section number (e.g., "5", "5 a") | |
| as_of_date | No | Historical date (YYYY-MM-DD). | |
| document_id | Yes | SFS number (e.g., "2018:218") or statute name (e.g., "dataskyddslagen") | |
| provision_ref | No | Provision reference: canonical "3:5" or Swedish "3 kap. 5 §". Alternative to chapter+section. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. While 'retrieve' implies a read operation, the description does not explicitly state that it's read-only, nor does it mention any behavioral traits like authentication needs, rate limits, or error handling. It is adequate but lacks explicit safety disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words. The first sentence states the purpose, and the second provides usage guidance. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters and no output schema, the description is minimal. It does not explain the return format, pagination (if any), or error scenarios. While the sibling context helps, more detail on what the response contains would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (all 5 parameters have descriptions in the schema). The tool description adds no additional parameter information beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a specific provision from a Swedish statute and explicitly distinguishes it from the sibling tool search_legislation, which is for keyword search. The verb 'retrieve' and resource 'specific provision' are precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Do NOT use for keyword search — use search_legislation instead,' providing clear when-not conditions and a direct alternative tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_provision_eu_basisA
Get EU legal basis for a specific provision. For statute-level EU references, use get_eu_basis instead.
| Name | Required | Description | Default |
|---|---|---|---|
| sfs_number | Yes | SFS number (e.g., "2018:218") | |
| provision_ref | Yes | Provision reference (e.g., "1:1" or "3:5") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, yet the description only states the basic function without disclosing behavioral traits such as read-only nature, required permissions, error handling, or response format. For a data retrieval tool, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, front-loading the purpose and immediately providing a clear alternative. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is minimal but covers the essential purpose and alternative. However, it lacks details about return values or behavior on errors, which could be useful given no output schema. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides detailed descriptions for both parameters (e.g., examples). The tool description adds no additional meaning beyond what is in the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'EU legal basis for a specific provision', and distinguishes from the sibling tool 'get_eu_basis' by noting it is for statute-level references.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool vs. an alternative: 'For statute-level EU references, use get_eu_basis instead.' This provides clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_provision_historyB
Returns the full version timeline for a specific provision of a Swedish statute. Shows all historical versions with validity dates. Premium feature — requires Ansvar Intelligence Portal.
| Name | Required | Description | Default |
|---|---|---|---|
| document_id | Yes | SFS number (e.g., "2018:218") or statute title | |
| provision_ref | Yes | Provision reference (e.g., "1:1", "3:2") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must cover behavioral traits. It mentions authentication requirements but does not state that the tool is read-only, has no side effects, or describe any limits or pagination behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences convey the core purpose and an important prerequisite. Concise and front-loaded, though could be slightly more structured (e.g., bullet points).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple read tool: it explains what it returns (version timeline with dates) and the auth requirement. However, without an output schema, it would benefit from describing the output format or structure (e.g., list of version objects with date fields).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are fully described in the schema (SFS number format and provision reference). The description does not add extra semantics beyond the schema, but with 100% coverage, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it returns the full version timeline for a provision of a Swedish statute, showing all historical versions with validity dates. This distinguishes it from sibling tools like get_provision (current version) and diff_provision (comparison).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Only mentions that it is a premium feature requiring the Ansvar Intelligence Portal, but does not provide guidance on when to use it versus alternatives (e.g., use this for history, get_provision for current text).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_recent_changesA
Lists all Swedish statute provisions that changed since a given date. Useful for regulatory change monitoring. Premium feature — requires Ansvar Intelligence Portal.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default: 50, max: 200) | |
| since | Yes | ISO date to look back from (e.g., "2024-01-01") | |
| document_id | No | Optional: filter to a specific statute by SFS number |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavior. It mentions 'Premium feature — requires Ansvar Intelligence Portal', but lacks details on what happens on unauthorized access, pagination, or the exact scope of changes (e.g., any text change vs. new provisions).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the core action, followed by use case and a critical requirement. Every sentence is necessary and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 3 parameters and no output schema. The description effectively communicates purpose, use case, and a key requirement (premium feature). However, it omits details about output format or how changes are defined, which could be useful but are not critical given the simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already explains each parameter adequately. The description adds no additional meaning beyond what is in the schema, aligning with the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Lists' and resource 'Swedish statute provisions that changed since a given date', clearly distinguishing it from sibling tools like search_legislation or get_provision_history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states it is 'Useful for regulatory change monitoring', implying the use case, but does not explicitly provide when-not-to-use or alternatives, which are not critical given the specificity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_swedish_implementationsA
Find Swedish statutes implementing a specific EU directive or regulation. For reverse (Swedish → EU), use get_eu_basis.
| Name | Required | Description | Default |
|---|---|---|---|
| primary_only | No | Return only primary implementing statutes | |
| in_force_only | No | Return only in-force statutes | |
| eu_document_id | Yes | EU document ID (e.g., "regulation:2016/679", "directive:95/46") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose behavioral traits like whether it is read-only, permissions needed, speed, or return format. Only states purpose and alternative, lacking transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with two sentences. First sentence states purpose, second provides alternative. No wasted words, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate but minimal. Does not describe output format or behavior beyond purpose. With 3 parameters and no output schema, more context could be beneficial, but the description meets basic needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described. Description does not add any additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool finds Swedish statutes implementing an EU directive/regulation. Specific verb 'Find' and resource 'Swedish statutes', and distinguishes from sibling get_eu_basis for the reverse direction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (find implementations of EU act) and provides an alternative for the reverse direction (use get_eu_basis).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_sourcesA
List all data sources used by this MCP server with provenance metadata.
Returns jurisdiction, source authorities, URLs, retrieval methods, update frequencies, licenses, coverage scope, and known limitations. Use this to understand where the data comes from and how current it is. For server statistics, use about instead.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It describes the output content but does not explicitly state that the tool is read-only, safe, or whether it requires authentication. For a straightforward list operation, this is minimally adequate but could be improved with a clear 'read-only' indication.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of only two sentences. The first sentence states the action and output fields, and the second provides usage guidance and sibling distinction. No fluff or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately covers the tool's purpose and output fields (jurisdiction, authorities, URLs, etc.) given the absence of an output schema. It could be slightly improved by mentioning if the list is exhaustive or paginated, but overall it is complete for a parameterless tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is 100%. With no parameters to describe, the description does not need to add parameter semantics. A baseline of 4 is appropriate since the schema fully covers the parameter space.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all data sources with provenance metadata, using a specific verb-resource combination. It distinguishes itself from the sibling 'about' by noting that 'about' is for server statistics, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises when to use this tool ('to understand where the data comes from and how current it is') and directs the agent to a specific alternative ('For server statistics, use about instead'). This provides clear context and differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_case_lawA
Search Swedish court decisions (rattsfall). FTS5 with BM25 ranking. Coverage depends on dataset tier — call 'about' to check actual case law count. Courts: HD, HFD, AD, RH, MÖD, MIG. Source: lagen.nu (CC-BY Domstolsverket). Do NOT use for statutes — use search_legislation instead.
| Name | Required | Description | Default |
|---|---|---|---|
| court | No | Filter by court code | |
| limit | No | Maximum results to return | |
| query | Yes | Search query for case law summaries | |
| date_to | No | End date filter (YYYY-MM-DD) | |
| date_from | No | Start date filter (YYYY-MM-DD) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description discloses the search algorithm (FTS5 with BM25 ranking), coverage dependency, and listed courts. While it doesn't mention rate limits or auth, it provides sufficient behavioral context for a read-only search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, with the most critical information (purpose and courts) first, and no redundant or off-topic content. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations or output schema, the description covers all key aspects: what it searches, ranking, coverage, available courts, source, and a critical negative directive. It is self-sufficient for an agent to decide when to invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes each parameter. The description adds overall context but does not significantly enhance individual parameter meanings beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches Swedish court decisions (rattsfall) with specific courts listed, and contrasts with search_legislation, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises against using for statutes and directs to search_legislation instead, plus suggests calling 'about' to check coverage. Provides clear when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_eu_implementationsA
Search EU directives/regulations with Swedish implementation info. Use get_swedish_implementations for specific EU document details.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Filter by document type | |
| limit | No | Maximum results to return | |
| query | No | Keyword search (title, short name, CELEX, description) | |
| year_to | No | Filter by year (to) | |
| community | No | Filter by EU community | |
| year_from | No | Filter by year (from) | |
| has_swedish_implementation | No | Only return EU documents with Swedish implementations |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the core function without disclosing behavioral traits such as authorization requirements, rate limits, or results ordering. For a search tool with multiple filters, basic behavioral context (e.g., fuzzy matching, case sensitivity) is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact with two sentences, no redundant words, and the main action is front-loaded. Every sentence serves a clear purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters and no output schema or annotations, the description provides a basic overview but lacks details on return format, pagination, or what 'Swedish implementation info' means. It is minimally adequate but leaves gaps for a tool with multiple filters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents all parameters. The description adds no additional meaning beyond repeating the tool's purpose. Baseline 3 is appropriate as the description does not hinder understanding but also does not enhance it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches EU directives/regulations with Swedish implementation info, using a specific verb ('Search') and resource ('EU directives/regulations'). It also distinguishes from the sibling tool 'get_swedish_implementations' by deferring specific details to that tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by naming an alternative tool ('Use get_swedish_implementations for specific EU document details'), helping the agent decide when to use this tool versus the sibling. However, it does not explicitly state when not to use this tool or cover other siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_legislationA
Search Swedish statutes and regulations by keyword. FTS5 with BM25 ranking. Do NOT use for case law — use search_case_law instead.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum results to return | |
| query | Yes | Search query in Swedish or English. Supports FTS5 syntax. | |
| status | No | Filter by document status | |
| as_of_date | No | Historical date filter (YYYY-MM-DD). | |
| document_id | No | Filter by SFS number (e.g., "2018:218") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions FTS5 with BM25 ranking, giving insight into search behavior and relevance scoring. While it doesn't cover all behavioral aspects (e.g., pagination, result format), it adequately communicates the core behavior for a read-only search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences with no wasted words. It front-loads the core purpose and includes critical usage guidance efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters and no output schema or annotations, the description provides sufficient context for an agent to use it correctly. Minor gaps exist (e.g., expected response structure), but the schema covers parameters well, and the search behavior is adequately described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% as all 5 parameters have descriptions. The description adds 'FTS5 with BM25 ranking', which enhances understanding of the 'query' parameter's behavior, but overall the schema already explains parameters sufficiently. Baseline score 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search Swedish statutes and regulations by keyword' with a specific verb and resource. It also explicitly distinguishes this tool from its sibling 'search_case_law', making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when not to use this tool: 'Do NOT use for case law — use search_case_law instead.' This directly addresses the primary alternative, helping the agent choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_citationA
Validate a Swedish legal citation against the database. Zero-hallucination enforcer. Do NOT use for formatting — use format_citation instead.
| Name | Required | Description | Default |
|---|---|---|---|
| citation | Yes | Citation string to validate (e.g., "SFS 2018:218 1 kap. 1 §") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Mentions 'zero-hallucination enforcer' which is a behavioral trait, but lacks details on side effects, error behavior, auth, or rate limits. Incomplete for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is extremely concise with three sentences. Front-loaded with purpose, followed by behavioral note and anti-guidance. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with one parameter and no output schema. Description lacks information about the output format or behavior (e.g., returns boolean or object). Adequate but could be more complete for an agent to anticipate result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with a clear example in the parameter description. Description adds no additional information beyond the schema, meriting baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool validates a Swedish legal citation against a database using a specific verb and resource. It distinguishes from sibling format_citation by explicitly directing not to use for formatting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-not-to-use guidance via warning against formatting and naming alternative format_citation. Implicitly indicates use for validation checks, but could be more explicit about other scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_eu_complianceA
Validate EU compliance status for a Swedish statute or provision. Phase 1: checks reference validity, not substantive compliance.
| Name | Required | Description | Default |
|---|---|---|---|
| sfs_number | Yes | SFS number (e.g., "2018:218") | |
| provision_ref | No | Provision reference (e.g., "1:1") | |
| eu_document_id | No | Check compliance with specific EU document (e.g., "regulation:2016/679") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It reveals a key limitation (only reference validity, not substantive compliance) but does not mention permissions, side effects, or error behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with two sentences, front-loading the core purpose and a key behavioral caveat. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and no annotations, the description is adequate but does not explain return values or error handling. It covers the basic functionality and a limitation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have descriptions in the schema (100% coverage). The tool description adds no additional meaning to the parameters beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates EU compliance for a Swedish statute, and specifies it is Phase 1 checking only reference validity. This is specific and differentiates from sibling tools that might check substantive compliance or retrieve EU basis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies through 'Phase 1' that further steps may be needed for full compliance, but does not explicitly state when to use this tool versus alternatives like get_eu_basis or search_eu_implementations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
19 tool updates
v1.2.5- First observed
about - First observed
build_legal_stance - First observed
check_currency - First observed
check_data_freshness - First observed
diff_provision - First observed
format_citation - First observed
get_eu_basis - First observed
get_preparatory_works - First observed
get_provision - First observed
get_provision_eu_basis - First observed
get_provision_history - First observed
get_recent_changes - First observed
get_swedish_implementations - First observed
list_sources - First observed
search_case_law - First observed
search_eu_implementations - First observed
search_legislation - First observed
validate_citation - First observed
validate_eu_compliance
TDQS
Scored across 19 tools
Every tool has a clear, distinct purpose with explicit cross-references and warnings to prevent misuse. For example, `search_legislation` and `search_case_law` are separated, and `get_provision` is not used for keyword search.
18 of 19 tools follow verb_noun pattern (e.g., `get_provision`, `search_legislation`, `validate_citation`). The sole exception is `about`, which is a common server metadata endpoint.
19 tools comprehensively cover Swedish legal research including statutes, case law, preparatory works, EU implementation, citations, validation, and history. Each tool earns its place without redundancy.
Core workflows are well-covered: search, retrieve provisions, validate, format, get history/diffs. Minor gap: no dedicated tool to retrieve full statute text or detailed case law document, but search and provision tools likely suffice for most use cases.
Maintenance
Related MCP Connectors
Riksdagen (Swedish Parliament) open data MCP.
MCP for CanLII: Canadian case law and legislation metadata (federal, provincial, territorial).
- LegalizeOAuthdev.legalize
Official MCP connector for Legalize: read and search its whole open corpus, at any point in time.
Resolve, search and verify legal citations against the official sources, with provenance.
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