# SEC EDGAR MCP Server — Insider Signals for AI Agents (`toolstem/toolstem-sec-mcp-server`) Actor SEC EDGAR MCP server for AI agents. Get insider trading signals (Form 4), 13F institutional holdings, 10-K/8-K filing velocity, and activist risk flags. No API key. Direct SEC data. - **URL**: https://apify.com/toolstem/toolstem-sec-mcp-server.md - **Developed by:** [Toolstem](https://apify.com/toolstem) (community) - **Categories:** AI, Developer tools, MCP servers - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 sec edgar queries 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 — Insider Signals, 13F Holdings & Filing Intelligence **SEC EDGAR intelligence for AI agents.** Five tools that answer the questions that matter: insider Form 4 trading signals, SC 13D activist risk flags, 10-K/8-K filing velocity, 8-K material event severity (RED/YELLOW/GREEN), and multi-company disclosure comparisons — all returned as structured JSON, direct from SEC EDGAR. No API key required. --- ### Why this exists Existing SEC data tools give agents paginated filing lists and raw XML. Agents then have to parse, classify, and derive signals themselves — burning context window on bureaucratic extraction instead of analysis. Toolstem SEC MCP Server pre-computes five high-value signals directly from SEC EDGAR's public submissions API, returning structured, agent-ready JSON. No third-party data providers, no API keys, no per-symbol fees — just SEC EDGAR's authoritative source with a rate-limiter that keeps you off their blocklist. --- ### The five tools #### 1. `get_company_filings_summary` Overview of a company's filing activity: last 20 filings + computed signals. | Signal | Description | |--------|-------------| | `filing_velocity` | `ACCELERATING` / `NORMAL` / `SLOWING` vs. trailing 365-day average | | `material_event_count_90d` | Count of 8-K filings in the last 90 days | | `disclosure_volume_trend` | `RISING` / `STABLE` / `FALLING` based on 10-K size comparison | | `latest_form_types` | Unique form types filed in the last 90 days | **Example output (abbreviated):** ```json { "ticker": "AAPL", "cik": "0000320193", "company_name": "Apple Inc.", "signals": { "filing_velocity": "NORMAL", "material_event_count_90d": 4, "disclosure_volume_trend": "RISING", "latest_form_types": ["8-K", "4", "DEF 14A"] }, "meta": { "source": "sec_edgar_direct", "data_delay": "live" } } ```` *** #### 2. `get_insider_signal` Probes Form 3/4/4A insider filing activity within a lookback window. Returns: `recent_insider_filings` (accession numbers + SEC URLs for Forms 3/4/4A), `lookback_days`, and counts. > **v0.1 note:** When at least one Form 3/4/4A filing exists in the lookback window, `insider_signal` is `null` ("direction unknown — Form 4 XML parsing ships in v0.2"). When no insider filings exist in the window, `insider_signal` is `"NEUTRAL"` ("verified absence of activity"). `buy_count` and `sell_count` are 0 in v0.1. **Example output (abbreviated):** ```json { "ticker": "MSFT", "cik": "0000789019", "company_name": "MICROSOFT CORP", "lookback_days": 90, "insider_signal": null, "net_transaction_count": 0, "buy_count": 0, "sell_count": 0, "recent_insider_filings": [ { "accession_number": "0001127602-26-001234", "filing_date": "2026-04-15", "sec_url": "https://www.sec.gov/Archives/edgar/data/789019/000112760226001234/0001127602-26-001234-index.htm" } ], "meta": { "source": "sec_edgar_direct", "data_delay": "live" } } ``` *** #### 3. `get_institutional_signal` Probes for activist investor activity via SC 13D / 13D/A filings. | Field | Description | |-------|-------------| | `activist_risk_flag` | `true` if any SC 13D or 13D/A was filed in the last 365 days | | `recent_13d_filings` | List of 13D filings with form type, date, and SEC URL | > **v0.1 note:** `institutional_signal` and `recent_13f_count` are null/0. Quarterly 13F XBRL/XML parsing (ACCUMULATING / HOLDING / DISTRIBUTING) ships in v0.2. **Example output (abbreviated):** ```json { "ticker": "NVDA", "cik": "0001045810", "company_name": "NVIDIA CORP", "quarters_back": 4, "institutional_signal": null, "recent_13f_count": 0, "activist_risk_flag": false, "recent_13d_filings": [], "meta": { "source": "sec_edgar_direct", "data_delay": "live" } } ``` *** #### 4. `get_material_events_digest` ⚡ premium ($0.50) Severity-ranked digest of all 8-K and 8-K/A filings within a lookback window. Maps each item code to a plain-English label and severity rating. | Severity | Examples | |----------|---------| | 🔴 RED | Cybersecurity incident (1.05), restatement (4.02), bankruptcy (1.03), delisting (3.01) | | 🟡 YELLOW | Acquisition (2.01), new debt (2.03), executive departure (5.02) | | 🟢 GREEN | Earnings release (2.02), Reg FD (7.01), shareholder vote (5.07) | Returns: `events[]` (sorted newest-first), `redflag_count`, `category_counts`. **Example output (abbreviated):** ```json { "ticker": "TSLA", "cik": "0001318605", "company_name": "Tesla, Inc.", "lookback_days": 180, "redflag_count": 1, "category_counts": { "RED": 1, "YELLOW": 3, "GREEN": 7 }, "events": [ { "accession_number": "0001628280-26-005678", "filing_date": "2026-04-10", "form": "8-K", "items": [ { "code": "4.02", "label": "Non-Reliance on Previously Issued Financial Statements", "category": "financial", "severity": "RED" } ], "sec_url": "https://www.sec.gov/Archives/edgar/data/1318605/000162828026005678/0001628280-26-005678-index.htm" } ], "meta": { "source": "sec_edgar_direct", "data_delay": "live" } } ``` *** #### 5. `compare_disclosure_signals` Side-by-side comparison of 2-5 companies across all key disclosure signals. All lookups run in parallel. Returns per-company: `filing_velocity`, `material_event_count_90d`, `redflag_count_365d`, `activist_risk_flag`, `last_filing_date`. Returns winners (as **CIKs**, not tickers — cross-reference with the `companies[]` array): `quietest_disclosure`, `most_active`, `most_redflags`, `activist_targets`. **Example output (abbreviated):** ```json { "companies": [ { "ticker": "AAPL", "cik": "0000320193", "filing_velocity": "NORMAL", "material_event_count_90d": 4, "redflag_count_365d": 0, "activist_risk_flag": false, "last_filing_date": "2026-04-25" }, { "ticker": "MSFT", "cik": "0000789019", "filing_velocity": "ACCELERATING", "material_event_count_90d": 7, "redflag_count_365d": 0, "activist_risk_flag": false, "last_filing_date": "2026-04-26" } ], "winners": { "quietest_disclosure": "0000320193", "most_active": "0000789019", "most_redflags": null, "activist_targets": [] }, "meta": { "source": "sec_edgar_direct", "data_delay": "live" } } ``` *** ### Pricing All calls are billed on a **per-result** basis via Apify's Pay-Per-Event (PPE) system. Pricing is charged at the time the tool returns its result. | Tool | Tier | Price per call | | --- | --- | --- | | `get_company_filings_summary` | Cheap | $0.005 | | `get_insider_signal` | Standard | $0.05 | | `get_institutional_signal` | Standard | $0.05 | | `get_material_events_digest` | Premium | $0.50 | | `compare_disclosure_signals` | Premium | $0.50 | Default-demo probes (Actor runs with no `tool` input) are **free** — they serve a cached result and do not fire a PPE charge. This keeps directory health-check probes and first-time evaluations cost-free. Apify retains a 20 % commission on all PPE revenue; the prices above are gross amounts. *** ### Installation #### npm (MCP stdio transport) ```bash npm install -g toolstem-sec-mcp-server ``` Add to your MCP client config (Claude Desktop, Cursor, etc.): ```json { "mcpServers": { "toolstem-sec": { "command": "toolstem-sec-mcp-server" } } } ``` No API key required. #### Hosted on Apify Run the Actor directly or connect via the MCP gateway: ``` https://mcp.apify.com/?tools=toolstem/toolstem-sec-mcp-server ``` Actor input example: ```json { "tool": "get_material_events_digest", "ticker_or_cik": "TSLA", "lookback_days": 365 } ``` #### HTTP server (self-hosted) ```bash npm install -g toolstem-sec-mcp-server toolstem-sec-mcp-server --http ## Listens on http://0.0.0.0:3000/mcp ``` *** ### SEC EDGAR fair-access policy All outbound traffic goes through a shared sliding-window rate limiter (8 rps target, 4 rps safety margin below SEC's 10 rps hard cap). Every request includes a `User-Agent` header identifying the package and a contact email per SEC policy. Override the contact email via: ```bash SEC_USER_AGENT_CONTACT=you@yourorg.com toolstem-sec-mcp-server ``` Violating SEC's fair-access policy can result in your IP being blocked. This server is designed to stay compliant automatically. *** ### v0.2 roadmap - **Form 4 XML parsing** — direction-aware insider signals (`STRONG_BUYING` / `BUYING` / `NEUTRAL` / `SELLING` / `STRONG_SELLING`) with net share counts - **13F XBRL parsing** — quarterly institutional flow signals (`ACCUMULATING` / `HOLDING` / `DISTRIBUTING`) with institution count - **8-K text extraction** — natural-language summaries of each material event from the filing's primary HTML document *** ### License & author MIT License — see [LICENSE](./LICENSE). Built by [Toolstem](https://github.com/toolstem). Data sourced directly from [SEC EDGAR](https://www.sec.gov/developer). # Actor input Schema ## `tool` (type: `string`): Which tool to run. Leave blank to run the no-charge default demonstration (get\_company\_filings\_summary for AAPL) — useful for first-time evaluators and directory health-check probes. For real usage, pick a tool and provide ticker\_or\_cik (or tickers\_or\_ciks for compare\_disclosure\_signals). ## `ticker_or_cik` (type: `string`): Company ticker symbol (e.g. AAPL) or CIK (e.g. 320193). Used by get\_company\_filings\_summary, get\_insider\_signal, get\_institutional\_signal, and get\_material\_events\_digest. ## `tickers_or_ciks` (type: `array`): 2-5 company tickers or CIKs for compare\_disclosure\_signals (e.g. \["AAPL", "MSFT", "GOOGL"]) ## `lookback_days` (type: `integer`): Days to look back for insider transactions (get\_insider\_signal) or material events (get\_material\_events\_digest). Default 90 / 365 respectively. ## `quarters_back` (type: `integer`): Quarters to look back for 13F holdings comparison (get\_institutional\_signal). Default 4. ## Actor input object example ```json { "ticker_or_cik": "AAPL" } ``` # 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 = { "ticker_or_cik": "AAPL" }; // Run the Actor and wait for it to finish const run = await client.actor("toolstem/toolstem-sec-mcp-server").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 = { "ticker_or_cik": "AAPL" } # Run the Actor and wait for it to finish run = client.actor("toolstem/toolstem-sec-mcp-server").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 '{ "ticker_or_cik": "AAPL" }' | apify call toolstem/toolstem-sec-mcp-server --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=toolstem/toolstem-sec-mcp-server", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEC EDGAR MCP Server — Insider Signals for AI Agents", "description": "SEC EDGAR MCP server for AI agents. Get insider trading signals (Form 4), 13F institutional holdings, 10-K/8-K filing velocity, and activist risk flags. No API key. Direct SEC data.", "version": "0.0", "x-build-id": "t5KwSSeVPDqWU5bnT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/toolstem~toolstem-sec-mcp-server/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-toolstem-toolstem-sec-mcp-server", "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/toolstem~toolstem-sec-mcp-server/runs": { "post": { "operationId": "runs-sync-toolstem-toolstem-sec-mcp-server", "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/toolstem~toolstem-sec-mcp-server/run-sync": { "post": { "operationId": "run-sync-toolstem-toolstem-sec-mcp-server", "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": { "tool": { "title": "Tool (optional)", "enum": [ "get_company_filings_summary", "get_insider_signal", "get_institutional_signal", "get_material_events_digest", "compare_disclosure_signals" ], "type": "string", "description": "Which tool to run. Leave blank to run the no-charge default demonstration (get_company_filings_summary for AAPL) — useful for first-time evaluators and directory health-check probes. For real usage, pick a tool and provide ticker_or_cik (or tickers_or_ciks for compare_disclosure_signals)." }, "ticker_or_cik": { "title": "Ticker or CIK", "type": "string", "description": "Company ticker symbol (e.g. AAPL) or CIK (e.g. 320193). Used by get_company_filings_summary, get_insider_signal, get_institutional_signal, and get_material_events_digest." }, "tickers_or_ciks": { "title": "Tickers or CIKs to Compare", "type": "array", "description": "2-5 company tickers or CIKs for compare_disclosure_signals (e.g. [\"AAPL\", \"MSFT\", \"GOOGL\"])", "items": { "type": "string" } }, "lookback_days": { "title": "Lookback (days)", "minimum": 1, "maximum": 1825, "type": "integer", "description": "Days to look back for insider transactions (get_insider_signal) or material events (get_material_events_digest). Default 90 / 365 respectively." }, "quarters_back": { "title": "Quarters Back", "minimum": 1, "maximum": 12, "type": "integer", "description": "Quarters to look back for 13F holdings comparison (get_institutional_signal). Default 4." } } }, "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 } } } } } } } } } } ```