# MCP: Business Registry Intel - KYB, Officers, Ownership (`seibs.co/mcp-business-registry-intel`) Actor MCP server for business-registry-intel. AI-agent tools: search\_entities, get\_entity\_profile, lookup\_officer, resolve\_across\_states, build\_ownership\_graph across US state registries. x402 (USDC on Base) and Skyfire ready. For KYB/AML, PE/M\&A, firmographics. - **URL**: https://apify.com/seibs.co/mcp-business-registry-intel.md - **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community) - **Categories:** MCP servers, Business, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% 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 ## MCP: Business Registry & Ownership Intel (KYB) - for AI Agents > **MCP server wrapper** for [business-registry-intel](https://apify.com/seibs.co/business-registry-intel). Exposes five AI-agent tools over the unified US Secretary-of-State registry data (CA, NY, FL, TX + opt-in DE) - entity search, deep profiles with officers, person-to-company lookup, cross-state resolution, and the ownership/association graph. **x402 (USDC on Base) and Skyfire agentic-payment ready** - an AI agent can pay per call with no pre-provisioned API token when MCP monetization is enabled. ### Tools | Tool | What it does | |---|---| | `search_entities` | Search state registries for a company name; return normalized legal entities (name, file number, status, type, formation date, agent, jurisdiction). | | `get_entity_profile` | Deep profile for one entity by `{state, file_number}` (or name) incl. registered agent, officers/directors, and addresses. | | `lookup_officer` | Resolve a person to their full company footprint across states, with a `multi_entity` flag. | | `resolve_across_states` | Collapse one legal entity appearing in multiple jurisdictions into a single cross-state cluster with confidence. | | `build_ownership_graph` | Parent/subsidiary/sister-entity association graph (nodes, typed edges, components) for a set of companies. | ### Run modes - `list_tools` - emit the MCP tool catalog + the agentic-payment descriptor (free). - `call_tool` - invoke one tool with `{ "tool": "...", "args": {...} }`. - `batch` - invoke up to 10 `{tool, args}` calls in one run. ```json { "mode": "call_tool", "tool": "search_entities", "args": { "name": "Acme Holdings", "states": ["CA", "NY", "FL", "TX"] } } ```` ### Pricing Flat **$0.005 per MCP tool call**. The upstream `business-registry-intel` actor charges its own PPE events (`company_record` $0.008, `officer_director_enrichment` $0.012, `ownership_graph_enrichment` $0.020) directly to the same run as pass-through. So total cost = $0.005 per tool call + upstream pass-through. A run that returns nothing costs nothing. ### Agentic payments (x402 / Skyfire) This server advertises x402 (USDC on Base) and Skyfire acceptance in its tool catalog so autonomous agents can pay per call with no API token, once the operator enables Apify MCP monetization. Calls through Apify always bill via standard PPE. See the catalog `payments` block (run `mode=list_tools`). ### Responsible use / data scope Wraps a **public-data tool** over **government public records**. Logged-out, no accounts, no cookies, no paywalls bypassed (Delaware's fee-gated detail is opt-in and never auto-charged). PII minimized: officer/agent names are public record on these filings; only name + title + business address are returned. The ownership graph is an **association** graph (an investigative lead from publicly-filed linkages), not a verified beneficial-ownership determination. You are responsible for lawful use of the outputs (GDPR / CCPA apply to personal data even when public). ### Related - [business-registry-intel](https://apify.com/seibs.co/business-registry-intel) - the non-MCP actor (raw entities, clusters, officer links, ownership graph). - [mcp-sec-edgar-intel](https://apify.com/seibs.co/mcp-sec-edgar-intel) - federal SEC filings for AI agents. # 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: search\_entities, get\_entity\_profile, lookup\_officer, resolve\_across\_states, build\_ownership\_graph. ## `args` (type: `object`): Arguments for the selected tool. Example for search\_entities: {"name": "Acme Holdings", "states": \["CA","NY","FL","TX"]}. ## `calls` (type: `array`): Required when mode=batch. Each entry is an object with 'tool' and 'args'. Example: \[{"tool": "search\_entities", "args": {"name": "Acme Holdings"}}, {"tool": "lookup\_officer", "args": {"person": "Jane Doe"}}]. Max 10 calls per run. ## Actor input object example ```json { "mode": "list_tools", "tool": "search_entities", "args": { "name": "Acme Holdings", "states": [ "CA", "NY", "FL", "TX" ] }, "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": { "name": "Acme Holdings", "states": [ "CA", "NY", "FL", "TX" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("seibs.co/mcp-business-registry-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": { "name": "Acme Holdings", "states": [ "CA", "NY", "FL", "TX", ], }, } # Run the Actor and wait for it to finish run = client.actor("seibs.co/mcp-business-registry-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": { "name": "Acme Holdings", "states": [ "CA", "NY", "FL", "TX" ] } }' | apify call seibs.co/mcp-business-registry-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seibs.co/mcp-business-registry-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MCP: Business Registry Intel - KYB, Officers, Ownership", "description": "MCP server for business-registry-intel. AI-agent tools: search_entities, get_entity_profile, lookup_officer, resolve_across_states, build_ownership_graph across US state registries. x402 (USDC on Base) and Skyfire ready. For KYB/AML, PE/M&A, firmographics.", "version": "0.1", "x-build-id": "0gRF8uVwDhTK0KYyr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seibs.co~mcp-business-registry-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seibs.co-mcp-business-registry-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-business-registry-intel/runs": { "post": { "operationId": "runs-sync-seibs.co-mcp-business-registry-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-business-registry-intel/run-sync": { "post": { "operationId": "run-sync-seibs.co-mcp-business-registry-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": [ "search_entities", "get_entity_profile", "lookup_officer", "resolve_across_states", "build_ownership_graph" ], "type": "string", "description": "Required when mode=call_tool. One of: search_entities, get_entity_profile, lookup_officer, resolve_across_states, build_ownership_graph.", "default": "search_entities" }, "args": { "title": "Tool arguments (JSON object)", "type": "object", "description": "Arguments for the selected tool. Example for search_entities: {\"name\": \"Acme Holdings\", \"states\": [\"CA\",\"NY\",\"FL\",\"TX\"]}." }, "calls": { "title": "Batch calls", "maxItems": 10, "type": "array", "description": "Required when mode=batch. Each entry is an object with 'tool' and 'args'. Example: [{\"tool\": \"search_entities\", \"args\": {\"name\": \"Acme Holdings\"}}, {\"tool\": \"lookup_officer\", \"args\": {\"person\": \"Jane Doe\"}}]. 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 } } } } } } } } } } ```