# SEC EDGAR MCP Server — Filings & Fundamentals for AI Agents (`commonelements/sec-edgar-mcp`) Actor MCP server (Streamable HTTP) exposing SEC EDGAR full-text search, company filings, RAG-ready filing chunks, and XBRL fundamentals as agent tools. Keyless official SEC data, citation-tagged. For Claude, Cursor, and any MCP client. - **URL**: https://apify.com/commonelements/sec-edgar-mcp.md - **Developed by:** [Harry Schoeller](https://apify.com/commonelements) (community) - **Categories:** AI, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 1,000 filing search / lists This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## SEC EDGAR MCP Server — Filings & Fundamentals for AI Agents An **MCP (Model Context Protocol) server** that gives Claude, Cursor, and any MCP-compatible AI agent direct, citation-tagged access to **official SEC EDGAR data** — full-text filing search, a company's filings, RAG-ready filing text chunks, and normalized XBRL fundamentals. It runs as an Apify **Standby** Actor speaking **MCP over Streamable HTTP** at `/mcp`. No API keys, no scraping gimmicks — just the SEC's keyless public endpoints, rate-limited under the official 10 requests/second ceiling with a compliant User-Agent. Keywords: **SEC MCP server**, SEC EDGAR for AI agents, Claude finance tool, Cursor SEC filings, 10-K / 10-Q / 8-K full-text search, XBRL fundamentals, RAG-ready SEC filings, financial research MCP. ### Tools | Tool | What it does | Key inputs | |---|---|---| | `search_filings` | Full-text search across **all** SEC filers (EFTS). | `query`, `forms?`, `since?`, `until?`, `limit?` | | `get_company_filings` | List one company's own filings with parsed Items. | `ticker?` or `cik?`, `forms?`, `since?`, `until?`, `limit?` | | `get_fundamentals` | Latest normalized XBRL fundamentals (revenue, net income, assets, EPS, cash flow…). Prefers annual 10-K figures. | `ticker?` or `cik?`, `concepts?` | | `get_filing_chunks` | Fetch one filing's primary document, clean it (inline-XBRL + tables resolved), segment by SEC Item, return token-budgeted, citation-tagged chunks. | `accessionNumber?` or `ticker?`+`form?`, `item?`, `maxChunks?`, `chunkSize?`, `chunkOverlap?` | | `resolve_company` | Resolve a ticker/CIK to `{ ticker, cik, companyName }`. | `ticker?` or `cik?` | Every record carries a human-readable `citation` string plus `deep_link` / `primaryDocUrl` / `filingIndexUrl` so an agent can ground and cite without a second lookup. Ticker **or** CIK is accepted everywhere. ### Connect an MCP client Once the Actor is running in Standby, its MCP endpoint is: ```` https://USERNAME--sec-edgar-mcp.apify.actor/mcp ```` with an `Authorization: Bearer ` header. #### Claude Desktop / Cursor (via `mcp-remote`) ```json { "mcpServers": { "sec-edgar": { "command": "npx", "args": [ "mcp-remote", "https://USERNAME--sec-edgar-mcp.apify.actor/mcp", "--header", "Authorization: Bearer ${APIFY_TOKEN}" ], "env": { "APIFY_TOKEN": "" } } } } ```` #### Native Streamable HTTP client Point the client at the `/mcp` URL above with the `Authorization` header. The server is **stateless** Streamable HTTP — no SSE. ### Example calls `get_fundamentals` for Apple: ```json { "ticker": "AAPL" } ``` returns the latest annual revenue (~$416B FY2025), net income, total assets, EPS, operating cash flow, and more — each tagged with the originating filing. `search_filings`: ```json { "query": "artificial intelligence", "forms": ["10-K"], "limit": 5 } ``` `get_filing_chunks` for Apple's latest 10-K, Risk Factors only: ```json { "ticker": "AAPL", "form": "10-K", "item": "1A", "maxChunks": 10 } ``` ### Pricing (pay per event) Charged once per successful, result-bearing tool call: | Event | Tools | Price (USD) | |---|---|---| | `filing-search` | `search_filings`, `get_company_filings` | $0.02 | | `fundamentals` | `get_fundamentals` | $0.03 | | `filing-chunks` | `get_filing_chunks` | $0.05 | | `resolve` | `resolve_company` | $0.005 | Failed or empty calls are not billed. ### Configuration Standby Actors take no per-run input. Configure via environment variable: - `SEC_USER_AGENT_EMAIL` — contact email sent in the SEC User-Agent header (default `admin@commonelements.com`). The SEC requires a descriptive User-Agent; set this to a real contact. In the Apify Console: enable **Standby** (suggested min 256 / max 1024 MB, 300s idle timeout) and set the monetization model to **Pay per event** pointing at `.actor/pay_per_event.json`. ### Data sources (all keyless, official) - `company_tickers.json` — ticker → CIK - `data.sec.gov/submissions/...` — filing listings - `efts.sec.gov/LATEST/search-index` — full-text search - `www.sec.gov/Archives/...` — filing documents - `data.sec.gov/api/xbrl/...` — XBRL fundamentals This Actor is unaffiliated with the U.S. Securities and Exchange Commission. # Actor input Schema ## Actor input object example ```json {} ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("commonelements/sec-edgar-mcp").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("commonelements/sec-edgar-mcp").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call commonelements/sec-edgar-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=commonelements/sec-edgar-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEC EDGAR MCP Server — Filings & Fundamentals for AI Agents", "description": "MCP server (Streamable HTTP) exposing SEC EDGAR full-text search, company filings, RAG-ready filing chunks, and XBRL fundamentals as agent tools. Keyless official SEC data, citation-tagged. For Claude, Cursor, and any MCP client.", "version": "0.1", "x-build-id": "g7rzBsN5pBepULoOy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/commonelements~sec-edgar-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-commonelements-sec-edgar-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/commonelements~sec-edgar-mcp/runs": { "post": { "operationId": "runs-sync-commonelements-sec-edgar-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/commonelements~sec-edgar-mcp/run-sync": { "post": { "operationId": "run-sync-commonelements-sec-edgar-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": {} }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```