# Startup Funding & Investor Intel - MCP Server (`seibs.co/mcp-startup-funding-intel`) Actor MCP server for startup-funding-intel. AI-agent tools for fresh funding rounds, investors, and momentum synthesized from SEC Form D, press, and hiring signals. x402 (USDC on Base) and Skyfire ready. For VC/PE, B2B sales, and recruiters. - **URL**: https://apify.com/seibs.co/mcp-startup-funding-intel.md - **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community) - **Categories:** AI, Business, Lead generation - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $5.00 / 1,000 mcp tool calls This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## Startup Funding & Investor Intel - MCP Server > Model Context Protocol (MCP) server wrapper for [startup-funding-intel](https://apify.com/seibs.co/startup-funding-intel). Gives AI agents direct, pay-per-call access to fresh SEC Form D funding rounds, company funding history, and investor portfolios - no API token required when called over x402 / Skyfire. ### What it is A thin MCP server that exposes the funding-intel engine as four typed tools an AI agent can call. Each tool runs the upstream `startup-funding-intel` actor (which rebuilds Crunchbase-grade funding data from PRIMARY public sources - SEC Form D filings via EDGAR plus press corroboration) and reshapes the result into small, deterministic JSON (no raw Form D XML, no megabyte press blobs). Built for deal-sourcing copilots, VC research agents, and B2B-sales bots that treat a fresh raise as a budget signal. ### Tools | Tool | What it does | |---|---| | `get_recent_rounds` | Fresh Form D funding rounds in a lookback window (default 14 days), filterable by industry group, issuer state, and minimum offering amount. | | `get_company_funding` | A named company's full Form D history plus a per-issuer rollup (total disclosed raised, round count, first/last filing dates, latest-round summary). | | `get_investor_portfolio` | An investor/person's Form D portfolio graph: companies backed, co-investors seen on the same filings, total disclosed, date range. | | `find_fresh_raises` | Screen 1-25 companies, return only those that filed a Form D within the lookback window (newest first) with a summary naming who raised. The fresh-raise = budget sales-trigger tool. | Every tool returns the same envelope: `{ tool, args, ok, count, items, summary, error }`. Agents key off `summary` for natural-language framing and `items` for structured downstream use. ### Run modes - `list_tools` - emit the tool catalog (free, no charge) including the agentic-payment descriptor. - `call_tool` - invoke one tool. Requires `tool` + `args`. - `batch` - invoke up to 10 `{tool, args}` calls in one run. ```json { "mode": "call_tool", "tool": "find_fresh_raises", "user_agent_contact": "you@company.com", "args": { "companies": ["Anthropic", "Mistral AI", "Cohere"], "lookback_days": 90 } } ```` ### Contact email is required (SEC fair-access) The SEC fair-access policy requires every automated EDGAR request to identify itself with a real contact email in the User-Agent, or the IP gets banned. Every tool here therefore requires a `contact_email`. Supply it once at the top level via `user_agent_contact`, or per call inside `args.contact_email` (the per-call value wins). The wrapper validates that it looks like an email and threads it into the upstream actor's `user_agent_contact`. Use your real contact - a fake or example.com identity routes the upstream actor to demo mode. ### Honest framing: Form D filing lag Form D is the SEC notice for a Regulation D exempt offering. It usually files **days to weeks after** a round is announced in the press, and the `filing_date` is the SEC notice date, not necessarily the close date. When present, `date_of_first_sale` is closer to the economic event. Every record carries a `data_lag_note` saying so. A company can also raise without ever filing a Form D, so absence of a filing is not proof a company did not raise. ### Agentic payments (x402 + Skyfire) This server is **x402 (USDC on Base)** and **Skyfire** ready. When the operator enables Apify MCP monetization, an AI agent can pay per tool call with no pre-provisioned API token. The `list_tools` response includes a `payments` descriptor advertising the accepted rails and per-call price. Operators enable rails via environment variables: | Env | Purpose | |---|---| | `X402_ENABLED` | `1` to advertise x402 acceptance | | `X402_PAY_TO_ADDRESS` | receiving wallet (USDC on Base) | | `X402_PRICE_USD` | per-call price advertised (default 0.005) | | `SKYFIRE_ENABLED` | `1` to advertise Skyfire acceptance | | `SKYFIRE_SELLER_ID` | Skyfire seller identity | Calls through Apify always bill via standard PPE (`mcp_tool_call` $0.005 + upstream pass-through); x402/Skyfire are the token-less rails layered on top for direct agents. ### Pricing Flat **$0.005 per MCP tool call**, plus the upstream `startup-funding-intel` PPE pass-through (`company_record` $0.006, `funding_round_record` $0.010, `investor_graph_enrichment` $0.012) billed to the same run. `mode=list_tools` is free. ### Responsible use / data scope The upstream actor reads only logged-out, public, government-source data: SEC Form D filings via EDGAR full-text search, the EDGAR archives, and press corroboration from public Google News RSS. No accounts, no cookies, no paywall bypass. PII is minimized - the data is company-level firmographics plus the issuer's disclosed control persons (a public-record field of the filing), not consumer data. Form D does not name LP/VC funds, so investor graphs reflect disclosed control persons, not fund investors. You are responsible for lawful use of the outputs. ### Related Actors - [startup-funding-intel](https://apify.com/seibs.co/startup-funding-intel) - the non-MCP actor with full input controls, monitor mode, and CSV/HTML artifacts. - [mcp-sec-edgar-intel](https://apify.com/seibs.co/mcp-sec-edgar-intel) - the broader SEC EDGAR MCP server (8-Ks, Form 4 insider trades, 13F, earnings transcripts). - [b2b-sales-triggers](https://apify.com/seibs.co/b2b-sales-triggers) - turn a fresh raise into an outbound sales trigger. ### Found this useful? Leave a quick review: https://apify.com/seibs.co/mcp-startup-funding-intel#reviews ### Changelog See [CHANGELOG.md](./CHANGELOG.md). # Actor input Schema ## `mode` (type: `string`): list\_tools = emit the MCP tool catalog (free). call\_tool = invoke one tool (requires 'tool' + 'args'). batch = invoke a list of {tool, args} calls. ## `tool` (type: `string`): Required when mode=call\_tool. One of: get\_recent\_rounds, get\_company\_funding, get\_investor\_portfolio, find\_fresh\_raises. ## `user_agent_contact` (type: `string`): A real contact email. The SEC fair-access policy requires every automated EDGAR request to identify itself with a contact email or the IP is banned. The wrapper threads this into the upstream actor's User-Agent. Used as the default for every tool call; a per-call args.contact\_email overrides it. Example: 'you@company.com'. ## `args` (type: `object`): Arguments for the selected tool (mode=call\_tool). Include contact\_email here, or set user\_agent\_contact above. Example for find\_fresh\_raises: {"contact\_email": "you@company.com", "companies": \["Anthropic", "Mistral AI", "Cohere"], "lookback\_days": 90}. ## `calls` (type: `array`): Required when mode=batch. Each entry is an object with 'tool' and 'args'. Set contact\_email once via user\_agent\_contact above, or per call inside args. Example: \[{"tool": "get\_recent\_rounds", "args": {"industry\_groups": \["Technology"]}}, {"tool": "get\_company\_funding", "args": {"company": "Anthropic"}}]. Max 10 calls per run. ## Actor input object example ```json { "mode": "list_tools", "tool": "find_fresh_raises", "user_agent_contact": "", "args": { "companies": [ "Anthropic", "Mistral AI", "Cohere" ], "lookback_days": 90 }, "calls": [] } ``` # 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 = { "mode": "list_tools", "args": { "companies": [ "Anthropic", "Mistral AI", "Cohere" ], "lookback_days": 90 } }; // Run the Actor and wait for it to finish const run = await client.actor("seibs.co/mcp-startup-funding-intel").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 = { "mode": "list_tools", "args": { "companies": [ "Anthropic", "Mistral AI", "Cohere", ], "lookback_days": 90, }, } # Run the Actor and wait for it to finish run = client.actor("seibs.co/mcp-startup-funding-intel").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 '{ "mode": "list_tools", "args": { "companies": [ "Anthropic", "Mistral AI", "Cohere" ], "lookback_days": 90 } }' | apify call seibs.co/mcp-startup-funding-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seibs.co/mcp-startup-funding-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Startup Funding & Investor Intel - MCP Server", "description": "MCP server for startup-funding-intel. AI-agent tools for fresh funding rounds, investors, and momentum synthesized from SEC Form D, press, and hiring signals. x402 (USDC on Base) and Skyfire ready. For VC/PE, B2B sales, and recruiters.", "version": "0.1", "x-build-id": "tUqCvj7OFQ9AVrviY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seibs.co~mcp-startup-funding-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seibs.co-mcp-startup-funding-intel", "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/seibs.co~mcp-startup-funding-intel/runs": { "post": { "operationId": "runs-sync-seibs.co-mcp-startup-funding-intel", "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/seibs.co~mcp-startup-funding-intel/run-sync": { "post": { "operationId": "run-sync-seibs.co-mcp-startup-funding-intel", "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", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "list_tools", "call_tool", "batch" ], "type": "string", "description": "list_tools = emit the MCP tool catalog (free). call_tool = invoke one tool (requires 'tool' + 'args'). batch = invoke a list of {tool, args} calls.", "default": "list_tools" }, "tool": { "title": "Tool name", "enum": [ "get_recent_rounds", "get_company_funding", "get_investor_portfolio", "find_fresh_raises" ], "type": "string", "description": "Required when mode=call_tool. One of: get_recent_rounds, get_company_funding, get_investor_portfolio, find_fresh_raises.", "default": "find_fresh_raises" }, "user_agent_contact": { "title": "Contact email (REQUIRED - SEC fair-access)", "type": "string", "description": "A real contact email. The SEC fair-access policy requires every automated EDGAR request to identify itself with a contact email or the IP is banned. The wrapper threads this into the upstream actor's User-Agent. Used as the default for every tool call; a per-call args.contact_email overrides it. Example: 'you@company.com'.", "default": "" }, "args": { "title": "Tool arguments (JSON object)", "type": "object", "description": "Arguments for the selected tool (mode=call_tool). Include contact_email here, or set user_agent_contact above. Example for find_fresh_raises: {\"contact_email\": \"you@company.com\", \"companies\": [\"Anthropic\", \"Mistral AI\", \"Cohere\"], \"lookback_days\": 90}." }, "calls": { "title": "Batch calls", "maxItems": 10, "type": "array", "description": "Required when mode=batch. Each entry is an object with 'tool' and 'args'. Set contact_email once via user_agent_contact above, or per call inside args. Example: [{\"tool\": \"get_recent_rounds\", \"args\": {\"industry_groups\": [\"Technology\"]}}, {\"tool\": \"get_company_funding\", \"args\": {\"company\": \"Anthropic\"}}]. Max 10 calls per run.", "default": [] } } }, "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 } } } } } } } } } } ```