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titusblair

edgar-mcp

by titusblair

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    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables searching SEC EDGAR for companies, retrieving recent filings (e.g., 10-K, 10-Q), and accessing structured XBRL financial facts.
      6 npm
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    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables LLMs to access SEC EDGAR data: search filings, extract sections, pull structured financials, and track insider transactions.
      24 npm
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    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables LLMs to download, parse, and analyze SEC EDGAR filings, including 10-K/Q reports, XBRL financial statements, and insider trading data. It provides structured access to institutional holdings, corporate events, and financial facts for comprehensive investment research.
      5
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    • A
      license
      A
      quality
      B
      maintenance
      Provides access to SEC EDGAR financial data, enabling AI agents to fetch company filings, financial metrics, and narrative sections. It supports natural-language metric searching and extracts structured data from 10-K, 10-Q, and 8-K reports.
      6
      24 PyPI
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Query SEC EDGAR for company filings, financial data, and executive disclosures. Search by company name or ticker, retrieve 10-K/10-Q/8-K filings, and extract structured financials — backed by the official SEC EDGAR API, built for AI agents.
      4
      MIT
    • A
      license
      B
      quality
      B
      maintenance
      Enables LLMs to process, validate, and analyze XBRL financial filings with tools for filing operations, fact extraction, taxonomy exploration, and SEC EDGAR integration.
      46
      Apache 2.0

    TDQS

    A4.3/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool serves a clearly distinct purpose: company resolution (find_company), filing listing (list_filings), section listing (list_filing_sections), section reading (read_filing_section), structured financial data (get_financial_facts), and full-text search (search_filings). There is no overlap; even list_filings and search_filings address different discovery needs (known company vs. unknown company).

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (find_company, list_filings, list_filing_sections, read_filing_section, get_financial_facts, search_filings). The pattern is uniform and clearly reflects the action each tool performs.

    Tool Count5/5

    Six tools is well-scoped for an EDGAR MCP server. Each tool covers a distinct part of the workflow (entity resolution, filing discovery, structure inspection, content reading, structured data extraction, and cross-company search) without redundancy or unnecessary bulk.

    Completeness5/5

    The tool surface covers the core EDGAR workflows end-to-end: finding a company, listing its filings, inspecting filing structure, reading specific sections, extracting structured financial facts, and searching across all filings. There are no obvious dead ends; the chain from find_company → list_filings → list_filing_sections → read_filing_section is complete, and get_financial_facts provides a reliable alternative for numerical data.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues