irish-competition-mcp
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., "@irish-competition-mcpFind CCPC decisions related to cartel enforcement."
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.
Irish Competition MCP
▶ Try this MCP instantly via Ansvar Gateway
50 free queries/day · no card required · OAuth signup at ansvar.eu/gateway
One endpoint, one OAuth signup, access from any MCP-compatible client.
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 flow at ansvar.eu/gateway. 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).
Irish competition data for AI compliance tools.
Query Irish competition data -- regulations, decisions, and requirements from CCPC (Competition and Consumer Protection Commission) -- directly from Claude, Cursor, or any MCP-compatible client.
Built by Ansvar Systems -- Stockholm, Sweden
Related MCP server: greek-competition-mcp
Available Tools (6)
Tool | Description |
| Full-text search across CCPC enforcement decisions (abuse of dominance, cartel, sector inquiries). Returns matching d... |
| Get a specific CCPC decision by case number (e.g., |
| Search CCPC merger control decisions (Fusionskontrolle). Returns merger cases with acquiring party, target, sector, a... |
| Get a specific merger control decision by case number (e.g., |
| List all sectors with CCPC enforcement activity, including decision counts and merger counts per sector. |
| Return metadata about this MCP server: version, data source, coverage, and tool list. |
All tools return structured data with source references and timestamps.
Data Sources and Freshness
All content is sourced from official Irish regulatory publications:
CCPC (Competition and Consumer Protection Commission) -- Official regulatory authority
Data Currency
Database updates are periodic and may lag official publications
Freshness checks run via GitHub Actions workflows
Last-updated timestamps in tool responses indicate data age
See sources.yml for full provenance metadata.
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 |
Dependabot | Automated dependency updates | Weekly |
See SECURITY.md for the full policy and vulnerability reporting.
Important Disclaimers
Not Regulatory Advice
THIS TOOL IS NOT REGULATORY OR LEGAL ADVICE
Regulatory data is sourced from official publications by CCPC (Competition and Consumer Protection Commission). However:
This is a research tool, not a substitute for professional regulatory counsel
Verify all references against primary sources before making compliance decisions
Coverage may be incomplete -- do not rely solely on this for regulatory research
Before using professionally, read: DISCLAIMER.md | PRIVACY.md
Confidentiality
Queries go through the Claude API. For privileged or confidential matters, use on-premise deployment. See PRIVACY.md for details.
Development
Setup
git clone https://github.com/Ansvar-Systems/irish-competition-mcp
cd irish-competition-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 build:db # Rebuild SQLite database from seed data
npm run check-updates # Check for new regulatory dataMore Ansvar MCPs
Full fleet at ansvar.eu/gateway.
Contributing
Contributions welcome! See CONTRIBUTING.md for guidelines.
License
Apache License 2.0. See LICENSE for details.
Data Licenses
Regulatory data sourced from official government publications. See sources.yml for per-source licensing details.
About Ansvar Systems
We build AI-powered compliance and legal research tools for the European market. Our MCP fleet provides structured, verified regulatory data to AI assistants -- so compliance professionals can work with accurate sources instead of guessing.
ansvar.eu -- Stockholm, Sweden
Available Tools
6 toolsie_comp_aboutA
Return metadata about this MCP server: version, data source, coverage, and tool list.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosure. It explicitly states the output includes version, data source, coverage, and tool list, making it clear this is a read-only metadata operation. No hidden side effects or destructive behavior are implied, and the description is honest about its scope.
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 a single sentence, front-loaded with the verb and resource, and lists the four key metadata items. Every word earns its place; there is no redundancy or filler.
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 about tool with no parameters, the description fully covers the purpose and return value. The lack of an output schema is mitigated by the explicit enumeration of returned fields. Complexity is low, and no additional context is needed for an agent to invoke this tool correctly.
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 baseline for 0 params is 4. The description adds value beyond the empty schema by specifying what the tool returns, which is the entire semantic content. No parameter details are needed, and the description fully compensates for the void in the schema.
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 ('Return') and identifies a clear resource ('metadata about this MCP server') with enumerated contents (version, data source, coverage, tool list). This clearly distinguishes it from sibling tools like ie_comp_search_decisions and ie_comp_get_decision, which are domain-specific data access tools.
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 clearly implies when to use this tool: when you need server-level metadata or a tool list. While it doesn't explicitly state exclusions or alternatives, the sibling tools are all about decisions/mergers/sectors, so the context is unambiguous. A dedicated 'about' tool is self-explanatory.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ie_comp_get_decisionA
Get a specific CCPC decision by case number (e.g., 'B6-22/16', 'B2-94/12').
| Name | Required | Description | Default |
|---|---|---|---|
| case_number | Yes | CCPC case number (e.g., 'B6-22/16', 'B2-94/12') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description discloses no behavioral traits such as read-only nature, response format, or error conditions. For a tool with no annotation coverage, the description carries the full burden, and it 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 a single sentence, front-loaded with the action, and includes concrete examples. Every word 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?
The tool is simple with one parameter, but lacks an output schema and annotations. The description does not explain what the response contains or behavior when the case number is not found. It is minimally acceptable but leaves gaps.
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 describes case_number with the same examples. The description adds no additional meaning beyond the schema, so it meets the baseline but does not exceed 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 a specific verb ('Get') and resource ('specific CCPC decision') and distinguishes from sibling search tools by specifying lookup by case number. It is unambiguous and concise.
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 usage when you know the case number, but it does not explicitly say to use a search tool when the case number is unknown. Sibling 'ie_comp_search_decisions' exists, but no alternative or exclusion is mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ie_comp_get_mergerA
Get a specific merger control decision by case number (e.g., 'B1-35/21', 'B8-101/18').
| Name | Required | Description | Default |
|---|---|---|---|
| case_number | Yes | CCPC merger case number (e.g., 'B1-35/21', 'B8-101/18') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states that it retrieves a decision, without detailing any behavioral traits such as error handling, return format, or permissions. The 'Get' verb implies a read operation, but no additional context is provided.
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 a single, clear sentence that front-loads the verb 'Get' and includes necessary examples. It is appropriately concise and readable.
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 is simple, with one parameter and no output schema. The description clearly states the purpose and parameter, making it sufficient for an agent to understand when to use it. However, it omits any detail about the response structure or potential errors, which is a minor gap.
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 full coverage with the same example strings ('B1-35/21', 'B8-101/18'). The description's examples duplicate the schema, so no new parameter meaning is added.
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 the specific verb 'Get' and identifies the resource as 'merger control decision' with the criteria 'by case number'. This clearly distinguishes it from sibling tools like search_mergers and get_decision, which have different purposes.
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 that this tool should be used when a specific case number is already known, but it does not explicitly state when to use alternatives or when not to use it. There is no mention of using search tools first or differentiating from get_decision for non-merger decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ie_comp_list_sectorsA
List all sectors with CCPC enforcement activity, including decision counts and merger counts per sector.
| 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 states the tool lists all sectors with activity and includes counts, giving useful behavioral detail. However, it does not disclose ordering, pagination, or any potential exclusions beyond 'with CCPC enforcement activity,' so it stops short of fully 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?
One sentence that is front-loaded and contains no waste. Every phrase adds meaning.
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 explains purpose and return data (counts per sector) despite lacking an output schema. For a simple zero-parameter list tool, this is adequately complete.
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 the baseline is 4. There is nothing to add beyond the schema.
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 identifies a specific verb ('List'), a clear resource ('sectors'), and a scope ('with CCPC enforcement activity'). It also specifies the output includes decision and merger counts, distinguishing it from sibling search/get tools that operate on individual decisions or mergers.
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 the appropriate use case (sector-level overview of enforcement activity) but does not explicitly mention alternatives or when not to use. It provides clear context without exclusions, earning a 4 per the rubric.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ie_comp_search_decisionsA
Full-text search across CCPC enforcement decisions (abuse of dominance, cartel, sector inquiries). Returns matching decisions with case number, parties, outcome, fine amount, and Competition Act articles cited.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Filter by decision type. Optional. | |
| limit | No | Maximum number of results to return. Defaults to 20. | |
| query | Yes | Search query (e.g., 'Marktmissbrauch', 'Facebook Nutzerdaten', 'Preisabsprache') | |
| sector | No | Filter by sector ID (e.g., 'digital_economy', 'grocery', 'financial_services'). Optional. | |
| outcome | No | Filter by outcome. Optional. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of indicating behavior. The words 'search' and 'returns' clearly imply a non-destructive read operation, and the return fields are disclosed. It does not mention rate limits or authentication, but for a search tool, the safety profile is adequately conveyed.
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 exactly two sentences, with the first stating the primary purpose and scope, and the second listing the return fields. It is front-loaded, precise, and contains no redundant 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 omits that the tool supports additional filters (type, sector, outcome, limit) and introduces a potential ambiguity: the schema includes 'merger' as a type, while the description lists only enforcement categories, suggesting mergers are out of scope. This mismatch should be explicitly clarified to avoid incorrect usage.
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 provides 100% descriptive coverage for all five parameters, so the description does not need to re-explain them. The tool description reinforces the type enum by listing examples in the text, but it adds no unique parameter-level detail beyond the schema.
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 a specific action (full-text search) on a well-defined resource (CCPC enforcement decisions), lists the covered categories (abuse of dominance, cartel, sector inquiries), and distinguishes from sibling merger search tools by explicitly limiting scope to enforcement decisions.
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 the tool's domain (enforcement decisions) and indirectly differentiates it from the sibling merger search tool, but it does not explicitly state when not to use it or name alternative tools. The scope is unambiguous enough for an agent to decide correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ie_comp_search_mergersA
Search CCPC merger control decisions (Fusionskontrolle). Returns merger cases with acquiring party, target, sector, and outcome.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return. Defaults to 20. | |
| query | Yes | Search query (e.g., 'Vonovia Deutsche Wohnen', 'Energieversorgung', 'Lebensmitteleinzelhandel') | |
| sector | No | Filter by sector ID (e.g., 'energy', 'food_retail', 'real_estate'). Optional. | |
| outcome | No | Filter by merger outcome. Optional. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. It does state that the tool 'returns merger cases' with specific fields, giving some behavioral insight. However, it omits details such as whether the search is read-only, how results are ordered, or any pagination or authorization requirements. This is acceptable but not rich.
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 a single, front-loaded sentence that states the tool's purpose and key output fields. It contains no filler or redundancy, making it highly concise 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?
For a search tool with four parameters and no output schema, the description provides a clear summary of return fields while the schema covers parameter details. It does not elaborate on interaction between filters (e.g., whether sector and outcome are combined), but the core usage is clear. This is reasonably complete.
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%, meaning each parameter (query, limit, sector, outcome) is documented in the schema. The description adds no additional parameter-level detail beyond what the schema already provides. Therefore, the description carries no extra semantic burden, netting a baseline '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 tool's function: 'Search CCPC merger control decisions (Fusionskontrolle).' It uses a specific verb ('search') and resource ('merger control decisions'), and distinguishes from sibling tools like ie_comp_search_decisions by focusing specifically on merger cases. The return fields ('acquiring party, target, sector, and outcome') further clarify scope.
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 the tool is for merger-specific searches, contrasting with more general decision search tools. It provides clear context (CCPC merger control) but does not explicitly state when not to use it or name alternatives. Since the sibling list suggests ie_comp_search_decisions for general decisions, the guidance is adequate but not fully explicit.
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.
6 tool updates
v0.1.0- First observed
ie_comp_about - First observed
ie_comp_get_decision - First observed
ie_comp_get_merger - First observed
ie_comp_list_sectors - First observed
ie_comp_search_decisions - First observed
ie_comp_search_mergers
TDQS
Scored across 6 tools
Each tool has a distinct purpose: search vs. get for decisions and mergers, plus list_sectors and about. There is no overlap or ambiguity between tools.
All tools share the 'ie_comp_' prefix and follow a clear verb_noun pattern (search_decisions, get_decision, search_mergers, get_merger, list_sectors). The 'about' tool is a conventional exception for metadata, but the pattern remains highly consistent.
Six tools is well-scoped for a read-only competition law database. Each tool serves a necessary function without redundancy or bloat.
The tool set covers the full lifecycle for this domain: search and retrieve both decisions and mergers, browse sectors, and access server metadata. As a read-only API, no create/update/delete operations are expected, so there are no obvious gaps.
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