@cyanheads/secedgar-mcp-server

Public Hosted Server: https://secedgar.caseyjhand.com/mcp

Tools

Eight tools for querying SEC EDGAR data, plus three for SQL analytics over the DuckDB-backed canvas dataframes those tools materialize:

secedgar_company_search

Entry point for most EDGAR workflows — resolve tickers, names, or CIKs to entity details.

• Supports ticker symbols (AAPL, VOO), company names (Apple), or CIK numbers (320193)

• ETFs and mutual funds resolve by ticker via company_tickers_mf.json; fund results include series_id and class_id for downstream scoping

• Current and former company names both resolve (Facebook → Meta Platforms, Square → Block)

• Near-match suggestions on zero-result name search (e.g. Microsfot → MICROSOFT CORP / MSFT)

• Optionally includes recent filings with form type filtering

• Date filtering (filed_after / filed_before) and under-filled form filters page into the older submissions archive, reaching filings that predate the ~1000-entry recent window (e.g. a 2005 10-K); history_scanned_through discloses the scan depth, and the full filtered history materializes as a df_<id> dataframe when it exceeds the inline filing_limit

• Returns entity metadata: SIC code, exchanges, fiscal year end, state of incorporation

secedgar_search_filings

Search EDGAR filings since 1993. Full-text search covers 2001-present (the EFTS index floor); pre-2001 date ranges are served from the archives — pre-2001 full-text matching requires entity scope.

• Exact phrases ("material weakness"), boolean operators (revenue OR income), wildcards (account*)

• Entity targeting within query string (cik:320193 or ticker:AAPL) — scoped server-side by CIK, so filings made under a former company name (same CIK) are included

• Browse mode: omit query to list filings by form type (forms=["S-1"]) and/or entity (ticker:/cik:), optionally narrowed by date — a bare date range is not a valid search and must be paired with forms or entity targeting

• Pre-2001 date ranges (back to 1993) route to the archives: an entity-scoped range reads the filer's full submissions history; an unscoped forms/date range browses the quarterly full-index. A range straddling 2001-01-01 is rejected with a split instruction, and pre-2001 full-text (no entity scope) is unsupported. Each row carries a source field (efts / submissions / full-index), preserved into the df_<id> dataframe

• Date range filtering, form type filtering, pagination up to 10,000 results

• Returns form distribution for narrowing follow-up searches

• When the entity-scoped window exceeds the inline limit, the already-fetched EFTS window is materialized as a df_<id> dataframe — query it with secedgar_dataframe_query

secedgar_get_filing

Fetch a specific filing's metadata and document content by accession number.

• Accepts accession numbers in dash or no-dash format

• Converts HTML filings to readable plain text

• Configurable content limit (1K–200K characters, default 50K)

• Can fetch specific exhibits by document name

• Offset paging for large documents (10-K, S-1/A can exceed 1M chars): pass next_offset from a truncated response as offset on the next call to continue reading; first-page truncated responses include a detected outline (headings with offsets) for targeted navigation

• Section targeting via the section param: jumps directly to a named heading by case-insensitive substring match (e.g. "risk factors", "item 7", "certain relationships"); on a miss, the error carries the detected outline so you can pick the correct heading

• Extracted text is cached per accession + document (bounded LRU, 8 entries), making subsequent paged calls cheap

secedgar_get_financials

Get historical XBRL financial data for a company with friendly concept name resolution.

• Friendly names like "revenue", "net_income", "eps_diluted" auto-resolve to correct XBRL tags

• Handles historical tag changes (e.g., ASC 606 revenue recognition)

• Automatic deduplication to one value per standard calendar period

• Filter by annual, quarterly, or all periods

• Optional limit caps the inline series to the most-recent N periods; the full series stays queryable via the df_<id> dataframe

• See secedgar://concepts resource for the full mapping

secedgar_get_insider_transactions

Surface Form 3/4/5 insider activity for a company by parsing ownership XML.

• Reporting person, relationship to issuer (director, officer + title, 10% owner), and transaction date

• Transaction code mapped to a readable type (purchase, sale, gift, award, exercise, …); shares signed by acquired/disposed

• Price per share and shares owned after each transaction; covers non-derivative (open-market) and derivative (option/RSU) lines

• Filter by transaction_type (purchase, sale, all); scans newest filings first

• The full set of transactions parsed from the scanned recent filings is materialized as a df_<id> dataframe (the inline list is a preview capped at limit) — query it with secedgar_dataframe_query to aggregate net buy/sell by insider

secedgar_get_institutional_holdings

Surface 13F-HR quarterly institutional holdings by parsing the information table.

• Pass the institutional filer (CIK or full legal name, e.g. 0000102909 for Vanguard) to see what it holds — reverse lookup from a portfolio company to its holders is not supported (EDGAR has no issuer→13F index); use secedgar_search_filings with forms=["13F-HR"] for issuer-side questions

• Each holding: issuer name, CUSIP, market value (whole USD), shares/principal, and put/call; raw rows also carry investment discretion

• Sub-lines for the same security (one per manager/account) are consolidated into distinct positions sorted by value by default — pass consolidate: false for raw filing rows

• Resolves the filing-manager name and reporting quarter from the cover page; target a specific quarter with quarter (e.g. "2025-Q4")

• total_holdings_in_filing counts raw info-table rows; total_positions counts distinct positions after consolidation (both before limit)

• The full parsed holdings set is materialized as a df_<id> dataframe (the inline list is a preview capped at limit) — query it with secedgar_dataframe_query for full-filing aggregation or cross-quarter joins on cusip + reporting_period

secedgar_fetch_frames

Fetch SEC XBRL frames for one concept × one period across all reporting companies.

• Same friendly concept names as secedgar_get_financials

• Supports annual (CY2023), quarterly (CY2024Q2), and instant (CY2023Q4I) periods

• Inline response returns the top N ranked companies (sort + limit), with ticker enrichment

• The full frames response (all reporters, typically 2k–10k rows) is materialized as a df_<id> dataframe — query it with secedgar_dataframe_query

• related_tags flags alternate-definition tags some filers use as their primary line (e.g. cash → restricted-cash-inclusive total, equity → NCI-inclusive total), so a whole-universe screen on the base tag isn't silently under-inclusive — query those separately

secedgar_search_concepts

Discover supported XBRL concept names before querying financials or cross-company comparisons.

• Search by friendly name, label, or raw XBRL tag

• Filter by statement group (income_statement, balance_sheet, cash_flow, per_share, entity_info) or taxonomy

• Reverse-lookup raw tags like NetIncomeLoss to the supported friendly names

• Surfaces related_tags for concepts with a high-coverage alternate-definition tag (e.g. restricted-cash-inclusive cash) so callers can discover them before screening

• Returns the same catalog used by secedgar_get_financials, secedgar_fetch_frames, and secedgar://concepts

secedgar_dataframe_describe / secedgar_dataframe_query / secedgar_dataframe_drop

In-conversation SQL analytics over the dataframes that secedgar_fetch_frames, secedgar_search_filings, secedgar_get_financials, secedgar_get_insider_transactions, and secedgar_get_institutional_holdings materialize on a shared DuckDB-backed canvas. Each data-returning call adds a dataset field with a df_XXXXX_XXXXX handle; pass that handle to secedgar_dataframe_query for joins, aggregates, window functions, percentiles — standard DuckDB SQL.

• Read-only by default. Writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected by the framework SQL gate. System catalogs (information_schema, pg_catalog, sqlite_master, duckdb_*) are denied at the bridge layer so callers can't enumerate dataframes they don't already hold a handle for. secedgar_dataframe_drop is the only destructive tool and is opt-in (EDGAR_DATAFRAME_DROP_ENABLED=true); TTL handles cleanup otherwise.

• Per-table TTL. Each dataframe ages on its own clock (default 24h, override with EDGAR_DATASET_TTL_SECONDS). The canvas itself uses the framework's sliding TTL.

• register_as chaining. secedgar_dataframe_query can persist its result as a new dataframe (df_XXXXX_XXXXX) with a fresh TTL — pipe analyses without re-running the source query.

Related MCP server: edgar-mcp

Resources

Prompts

Features

Built on @cyanheads/mcp-ts-core:

• Declarative tool definitions — single file per tool, framework handles registration and validation

• Structured output schemas with automatic formatting for human-readable display

• Unified error handling across all tools

• Pluggable auth (none, jwt, oauth)

• Structured logging with request-scoped context

• Runs locally (stdio/HTTP) from the same codebase

SEC EDGAR–specific:

• Rate-limited HTTP client respecting SEC's 10 req/s limit with automatic inter-request delay

• CIK resolution from tickers (including ETFs and mutual funds via company_tickers_mf.json), company names (current and former), or raw CIK numbers with local caching; near-match trigram suggestions on zero-result name queries; committed former-names.json asset for prior-name resolution (Facebook → Meta, Square → Block)

• Friendly XBRL concept name mapping with historical tag change handling

• Searchable concept catalog with statement-group metadata and reverse XBRL tag lookup

• HTML-to-text conversion for filing documents via html-to-text

• In-conversation SQL analytics: secedgar_fetch_frames, secedgar_search_filings, secedgar_get_financials, secedgar_get_insider_transactions, and secedgar_get_institutional_holdings materialize their full result as a DuckDB-backed canvas dataframe queryable via secedgar_dataframe_query

• No API keys required — SEC EDGAR is a free, public API

Getting started

Public Hosted Instance

A public instance is available at https://secedgar.caseyjhand.com/mcp — no installation required. Point any MCP client at it via Streamable HTTP:

{
  "mcpServers": {
    "secedgar-mcp-server": {
      "type": "streamable-http",
      "url": "https://secedgar.caseyjhand.com/mcp"
    }
  }
}

Self-Hosted / Local

Add the following to your MCP client configuration file.

{
  "mcpServers": {
    "secedgar-mcp-server": {
      "type": "stdio",
      "command": "bunx",
      "args": ["@cyanheads/secedgar-mcp-server@latest"],
      "env": {
        "EDGAR_USER_AGENT": "YourAppName your-email@example.com",
        "MCP_TRANSPORT_TYPE": "stdio"
      }
    }
  }
}

Or with npx (no Bun required):

{
  "mcpServers": {
    "secedgar-mcp-server": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@cyanheads/secedgar-mcp-server@latest"],
      "env": {
        "EDGAR_USER_AGENT": "YourAppName your-email@example.com",
        "MCP_TRANSPORT_TYPE": "stdio"
      }
    }
  }
}

For Streamable HTTP, set the transport and start the server:

MCP_TRANSPORT_TYPE=http MCP_HTTP_PORT=3010 bun run start:http
# Server listens at http://localhost:3010/mcp

Prerequisites

• Bun v1.3.0 or higher.

Installation

1. Clone the repository:

git clone https://github.com/cyanheads/secedgar-mcp-server.git

2. Navigate into the directory:

cd secedgar-mcp-server

3. Install dependencies:

bun install

4. Build:

bun run build

Configuration

All configuration is validated at startup via Zod schemas in src/config/server-config.ts. Key environment variables:

Running the server

Local development

• Build and run the production version:

  bun run rebuild
  bun run start:http   # or start:stdio

• Run checks and tests:

  bun run devcheck     # Lints, formats, type-checks
  bun run test         # Runs test suite

Docker

docker build -t secedgar-mcp-server .
docker run -e EDGAR_USER_AGENT="MyApp my@email.com" -p 3010:3010 secedgar-mcp-server

The image ships the mirror CLI, so the local mirror (EDGAR_MIRROR_ENABLED) can be bootstrapped, inspected, and refreshed inside a running container:

docker exec <container> bun run mirror:verify    # sync status + sample reads
docker exec <container> bun run mirror:init      # one-time bootstrap (downloads the SEC bulk archive)
docker exec <container> bun run mirror:refresh   # re-ingest when the archive has been rebuilt

Project structure

Development guide

See CLAUDE.md and AGENTS.md for development guidelines and architectural rules. The short version:

• Handlers throw, framework catches — no try/catch in tool logic

• Use ctx.log for logging, ctx.state for storage

• Register new tools and resources in the createApp() arrays

Contributing

Issues and pull requests are welcome. Run checks and tests before submitting:

bun run devcheck
bun run test

License

This project is licensed under the Apache 2.0 License. See the LICENSE file for details.