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Nordic Financial MCP

by io.github.AIDataNordic

search_filings

Read-only

Search the Nordic financial database for company filings, press releases and macroeconomic summaries.

Use this as the primary tool for any question about Nordic listed companies, markets or macro conditions. Do not use to retrieve a full document — results are chunked text excerpts; use parse_pdf_to_text for the full original document. Do not use for Swedish company registration data — use get_company_info instead.

The database contains ~1 million vectors across four Nordic markets (NO/SE/DK/FI).

COMPANY FILINGS Annual reports (XBRL/ESEF) and quarterly reports from ~1 500 listed companies across Oslo Børs, Nasdaq Stockholm, Nasdaq Helsinki, Nasdaq Copenhagen and First North markets. Covers 2020–present. Strong coverage for NO and SE; growing coverage for DK and FI.

EXCHANGE ANNOUNCEMENTS & PRESS RELEASES Regulatory filings, exchange announcements and press releases from listed companies in NO, SE, DK and FI. Covers 2020–present.

MACROECONOMIC SUMMARIES Quarterly macro summaries covering key indicators per country: Norway (NO): policy rate, FX rates, CPI, house prices, credit growth, electricity price, salmon price, GDP components Sweden (SE): policy rate, house price index, household credit Denmark (DK): policy rate, house price index, household loans, electricity price Finland (FI): house price index, household debt-to-income ratio, electricity price Use report_type='macro_summary' and country='NO'/'SE'/'DK'/'FI' to filter. Use fiscal_year and a quarter reference in your query, e.g. "Norwegian housing market Q1 2024".

Args: query: What you are looking for, e.g. 'net interest margin outlook', 'salmon price Q3', 'dividend policy', 'fleet utilization', 'Norwegian housing market 2024 Q1', 'Swedish policy rate inflation 2023' ticker: Optional — filter by company ticker, e.g. 'SALM', 'EQNR', 'NDA' fiscal_year: Optional — filter by year, e.g. 2024 report_type: Optional — one of: 'annual_report' – Nordic XBRL/ESEF annual reports 'quarterly_report' – Quarterly/interim reports 'press_release' – Exchange announcements and press releases 'macro_summary' – Quarterly macroeconomic summaries sector: Optional — filter by sector: 'seafood' – seafood companies 'energy' – energy / oil & gas 'shipping' – shipping companies country: Optional — filter by country code: 'NO', 'SE', 'DK' or 'FI' limit: Number of results after reranking (default 5, max 20)

Returns: List of relevant text excerpts with metadata, reranked by relevance. Each result includes rerank_score, hybrid_score, vector_score, company, ticker, country, fiscal_year, report_type, period, filing_date and the full text chunk. Returns an empty list if no relevant results are found or if the Qdrant database is temporarily unreachable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fastNoSkip reranking and return results ranked by hybrid score only. Faster but less precise.
limitNoNumber of results to return (1–20)
queryYesNatural language search query, e.g. 'Equinor dividend 2024' or 'Norwegian housing market Q3'
sectorNoFilter by sector, e.g. 'energy', 'financials', 'salmon'
sourceNoFilter by data source, e.g. 'xbrl_esef', 'newsweb', 'mfn_nordics', 'nasdaq_se'
tickerNoFilter by company ticker, e.g. 'EQNR', 'SALM', 'NDA'
countryNoFilter by country: NO, SE, DK, or FI
fiscal_yearNoFilter by fiscal year, e.g. 2024. Use 0 for no filter
report_typeNoFilter by type: annual_report, quarterly_report, press_release, exchange_announcement, macro_summary
max_chunk_indexNoOnly return chunks with chunk_index <= this value. Use 3 to target introductory sections of long documents. Use 0 for no filter.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Description aligns with readOnlyHint=true, indicating a safe read-only operation. It adds context: database contains ~1M vectors, results are chunked excerpts reranked by relevance, returns empty list if no results or database unreachable. No contradiction with annotations.

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 lengthy but well-structured with sections for different content types (COMPANY FILINGS, EXCHANGE ANNOUNCEMENTS, MACROECONOMIC SUMMARIES) and uses bullet points. Every sentence adds value given the complexity (10 params, multiple categories). Minor redundancy in some examples but overall efficient.

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 10 parameters, 1 required, full schema description, and no output schema in input (but has it according to context), the description covers all necessary aspects: database scope, parameter details, usage examples, return format, and error handling. It is complete for an agent to invoke correctly.

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%, and the description's Args section adds significant value with examples, allowed values, and context for each parameter. For instance, query examples include 'net interest margin outlook', 'Norwegian housing market Q4', and report_type options are listed with explanations. This exceeds what the schema alone provides.

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 the Nordic financial database for company filings, press releases, and macro summaries. It distinguishes from siblings by specifying it is the primary tool for Nordic-related queries and explicitly telling agents not to use it for full document retrieval (use parse_pdf_to_text) or Swedish company registration (use 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 Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use ('primary tool for questions about Nordic listed companies, markets or macro conditions') and when-not-to-use ('do not use to retrieve a full document', 'do not use for Swedish company registration data') with alternatives. Includes concrete examples for macro summaries and query patterns.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Nordic Financial MCP toolsInspect
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TDQS

A4.6/5.0
Disambiguation5/5

Each tool has a clear, distinct purpose: analyze_company for synthesized answers, company_research for raw grouped search results, search_filings for direct database queries, get_company_info for registry data, get_current_power_price for electricity prices, parse_pdf_to_text for full document extraction, and ping for connectivity. Descriptions explicitly differentiate them, preventing confusion.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case: analyze_company, company_research, get_company_info, get_current_power_price, parse_pdf_to_text, search_filings, and ping (a single word but acceptable). No mixing of conventions or inconsistent styles.

Tool Count5/5

Seven tools is well-scoped for a Nordic financial data server. Each tool serves a necessary function without redundancy or bloat. The count covers core data retrieval, analysis, registry lookup, niche data (power prices), and utility tools (PDF parsing, health check), fitting the server's purpose.

Completeness4/5

The tool set covers the main workflows: searching filings, analyzing companies, retrieving registry data, fetching power prices, and extracting full documents. A minor gap is the lack of a direct Swedish registry lookup (get_company_info excludes Sweden, and search_filings doesn't provide registration data). Otherwise, the surface is well-rounded for Nordic financial queries.

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