Nordic Financial MCP

Server Quality Checklist

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Latest release: v1.0.30
Disambiguation5/5
Each tool serves a uniquely defined purpose with no overlap. due_diligence_report is for batch DD searches, search_filings for general queries, get_company_info for registry data, get_current_power_price for spot prices, parse_pdf_to_text for PDFs, and ping for health checks. Descriptions clearly differentiate them.
Naming Consistency4/5
Most tools follow a verb_noun pattern (get_company_info, get_current_power_price, parse_pdf_to_text, search_filings). However, due_diligence_report is a noun phrase and ping is a single word, deviating slightly. Overall, the pattern is still descriptive and readable.
Tool Count5/5
With 6 tools, the server is well-scoped for a financial data domain. Each tool provides distinct functionality without redundancy, and the count feels appropriate for covering core operations (search, registry, power prices, PDF parsing, DD report, health check).
Completeness4/5
The tool set covers essential operations: searching filings/macro, retrieving registry info, fetching power prices, extracting PDFs, and running DD reports. Minor gaps exist, such as missing Swedish registry data and historical power price retrieval, but these are partially addressable via search_filings. Overall, it is fairly complete for its stated purpose.
Average 4.6/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 commits in the last 12 weeks
- Last stable release on April 28, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint true and openWorldHint false. The description adds behavioral details: each query runs as hybrid search, ticker filter to avoid false positives, and constraints on sections and limits. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear paragraphs, but it is slightly verbose. Could be more concise while retaining all critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity and presence of an output schema, the description covers input semantics, constraints, and rationale. It does not need to explain output format due to output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. The description adds significant value beyond the schema: explains the structure of sections, the importance of ticker, and default limit. This helps the agent use parameters correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Run multiple targeted searches and return results grouped by section for due diligence.' It uses specific verbs and nouns, and distinguishes itself from siblings like search_filings and get_company_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (due diligence) and provides guidance on how to formulate queries and use tickers. However, it does not explicitly mention when not to use it or name alternative siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true; the description adds context that the data is from an official registry and is authoritative, which aligns with and reinforces the annotations without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, front-loaded with the main purpose, each sentence providing essential guidance without any fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers scope, exclusions, and use cases adequately for a simple tool with an output schema; no missing details that affect correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage on both parameters, so the description adds minimal new meaning beyond repeating the country codes and identifier format already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Look up') and resource ('company in the official business registry'), and clearly distinguishes from siblings by explicitly stating not to use for Sweden (use search_filings) and not for tickers/ISIN.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states when to use (retrieve authoritative registration data for a known organisation number) and when not to use (for Sweden or tickers/ISIN), providing a specific alternative (search_filings with country='SE').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. Description adds valuable behavioral context: not suitable for scanned PDFs without embedded text, with specific output format ('(no extractable text)') for such pages.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each adding value: action, use case with combination, warning about alternatives, and limitation. No wasted words. Well-structured with front-loaded purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (context indicates true), the description explains return behavior (page-by-page, placeholder for non-text pages). Covers prerequisites, use cases, and limitations. Complete for a single-parameter tool with good annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter (pdf_url) with schema description 'Direct HTTPS URL to the PDF file'. Schema coverage is 100%, so description does not need to add much. Description does not repeat schema details, but it is acceptable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb (download and extract text), resource (PDF from URL), and scope (page by page). Distinguishes from sibling search_filings by stating it's for full text of a specific document.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (after search_filings for full text) and when not to use (if PDF is well-represented in database or is scanned). Names alternative (search_filings) and highlights speed advantage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds that the response is a greeting string with the provided name. No contradictions. While it doesn't elaborate on potential non-response behavior, it is sufficient for a simple ping tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loads the purpose, and every sentence adds value. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description fully covers the tool's purpose, usage context, limitations, and return value. For a simple connectivity check, it is complete and leaves no gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameter 'name' is already well-documented in the schema. The description adds no new semantic information beyond the schema, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a connectivity check, and the verb 'confirm' combined with 'server process is responding' specifies the exact resource and action. It distinguishes from siblings like search_filings which test data availability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises using at session start to verify reachability, warns against misuse as database proxy, and directs to search_filings for data health. 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true; description adds that results are chunked text excerpts, not full documents, and notes database size. No contradictions with annotations, but could further detail result structure or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is longer but well-structured with sections and bullet points. It is informative without verbosity; each part serves a purpose. Could be slightly tighter but the complexity justifies length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given existence of output schema, description covers domain, content types, exclusions, and filtering guidance thoroughly. Provides practical examples and business context for Nordic markets, making it complete for an agent to use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage, so baseline is 3. Description adds value with example queries, enumeration of report_types, and specific macro usage instructions, going beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool searches for company filings, press releases, and macroeconomic summaries in the Nordic financial database. It distinguishes itself from siblings by specifying when to use alternative tools (parse_pdf_to_text for full docs, get_company_info for Swedish registration).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises it as the primary tool for Nordic queries and provides clear exclusions: not for full documents (use parse_pdf_to_text) and not for Swedish company registration (use get_company_info). Also gives specific filter guidance for macro summaries with report_type and country.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond the annotations: it specifies data sources (NordPool, hvakosterstrommen.no, ENTSO-E), the unit (EUR/kWh), and the dynamic behavior of the 'tomorrow' field (returns 'not yet available' before 13:00 CET). The annotations (readOnlyHint, openWorldHint) are consistent with this read and variable-data nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by usage guidelines, timing, and data source details. Each sentence provides unique, essential information without redundancy. Despite five sentences, it remains efficient and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, output schema exists, annotations present), the description covers all necessary aspects: purpose, usage boundaries, timing constraints, data sources, units, and zone-specific behavior. The presence of an output schema relieves the description from explaining return values, making it fully sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with descriptions for both parameters. The description adds value by explaining zone-specific data sources (Norwegian zones use hvakosterstrommen.no, others use ENTSO-E), which contextualizes the 'zone' parameter beyond the schema's simple list. This extra information slightly exceeds the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Fetch today's hourly day-ahead electricity spot prices for a Nordic bidding zone,' which clearly states the verb ('fetch'), resource ('prices'), and scope ('today's hourly day-ahead'). It distinguishes from the sibling 'search_filings' by explicitly stating when not to use this tool and directing to the alternative for historical analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool ('current and near-term queries') and when not to ('historical analysis'), providing a clear alternative ('use search_filings with report_type='macro_summary''). It also includes timing constraints for tomorrow's prices (published after 13:00 CET) and the resulting behavior when not available.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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