# DataSignals Lab MCP: 13 Free Financial Data Tools for AI Agents (`datasignalslab/datasignals-mcp`) Actor Free MCP server: 13 scored financial data tools in one endpoint - insider trading, 13F, Form D startup funding, 8-K, FDA, Congress trades and more. - **URL**: https://apify.com/datasignalslab/datasignals-mcp.md - **Developed by:** [DataSignals Lab](https://apify.com/datasignalslab) (community) - **Categories:** AI, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## DataSignals Lab MCP: Financial and Market Data Tools for AI Agents **One MCP endpoint that gives your AI agent 13 scored, decision-ready data tools.** Connect Claude, ChatGPT, Cursor or any MCP client and let the agent pull insider trading, hedge-fund positioning, corporate events, biotech and FDA catalysts, government contracts, Congress trading, research funding, startup fundraising (Form D), crypto momentum and app review sentiment - on demand, with source links. This Model Context Protocol (MCP) server bundles the full DataSignals Lab suite behind a single connection, so an agent can call the right tool autonomously instead of you wiring up a dozen separate APIs. ### Tools | Tool | What it returns | Source | |---|---|---| | `insider_trading_clusters` | Clusters of insider open-market buying, scored 0-100 | SEC EDGAR Form 4 | | `insider_selling_form144` | Planned insider sales (seller, role, USD value), scored | SEC EDGAR Form 144 | | `hedge_fund_13f` | Hedge-fund buys, exits and cross-fund consensus | SEC EDGAR 13F | | `sec_8k_events` | Material 8-K events, classified and materiality-scored | SEC EDGAR 8-K | | `activist_stakes_13dg` | 5%+ stakes, activist (13D) vs passive (13G), scored | SEC EDGAR 13D/G | | `biotech_catalysts` | Upcoming trial readouts and phase changes, scored | ClinicalTrials.gov | | `fda_drug_actions` | FDA approvals and regulatory actions, scored | openFDA Drugs@FDA | | `government_contracts` | Recent federal contract wins and momentum, scored | USAspending.gov | | `congress_trading` | House member stock trades, parsed and scored | House Clerk disclosures | | `nih_research_funding` | NIH grant momentum by organization or topic | NIH RePORTER | | `startup_funding_form_d` | New capital raises before press coverage, fund noise filtered, scored | SEC EDGAR Form D | | `crypto_momentum_scanner` | Volume and momentum anomalies, scored | CoinGecko | | `app_review_intelligence` | App Store aspect sentiment and competitor comparison | Apple App Store | ### How to connect This Actor runs in Standby mode as a streamable HTTP MCP server. Point your MCP client at the Standby URL with the `/mcp` path and pass your own Apify API token: ```json { "mcpServers": { "datasignals-lab": { "url": "https://datasignalslab--datasignals-mcp.apify.actor/mcp", "headers": { "Authorization": "Bearer " } } } } ```` You can also reach it through Apify's hosted MCP gateway at `https://mcp.apify.com` by adding the Actor `datasignalslab/datasignals-mcp`. Live Actor listing: https://apify.com/datasignalslab/datasignals-mcp Then ask your agent things like "Which insiders are buying clusters this week?", "Show recent 8-K events for AAPL and TSLA", or "What did House members trade in NVDA?" and the agent will call the matching tool. ### Pricing Each tool runs the underlying DataSignals Lab Actor, which is pay-per-event (typically $0.20 per analyzed company, fund, scan or query). There is no separate subscription and no extra markup for using the bundle. ### Data and compliance All tools use official, public, non-personal sources (SEC EDGAR, openFDA, ClinicalTrials.gov, USAspending.gov, the House Clerk, NIH RePORTER, CoinGecko and the Apple App Store reviews feed). Output is data for research and monitoring, not investment advice. Historical patterns do not guarantee future results. # Actor input Schema ## Actor input object example ```json {} ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("datasignalslab/datasignals-mcp").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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("datasignalslab/datasignals-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 datasignalslab/datasignals-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datasignalslab/datasignals-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "DataSignals Lab MCP: 13 Free Financial Data Tools for AI Agents", "description": "Free MCP server: 13 scored financial data tools in one endpoint - insider trading, 13F, Form D startup funding, 8-K, FDA, Congress trades and more.", "version": "0.0", "x-build-id": "Engy0rQNhdZFnBJ8b" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datasignalslab~datasignals-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datasignalslab-datasignals-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datasignalslab~datasignals-mcp/runs": { "post": { "operationId": "runs-sync-datasignalslab-datasignals-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datasignalslab~datasignals-mcp/run-sync": { "post": { "operationId": "run-sync-datasignalslab-datasignals-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 } } } } } } } } } } ```