# How to integrate Companyenrich MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Companyenrich MCP with Vercel AI SDK v6", "toolkit": "Companyenrich", "toolkit_slug": "companyenrich", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/companyenrich/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/companyenrich/framework/ai-sdk.md", "updated_at": "2026-06-18T09:19:53.734Z" } ``` ## Introduction This guide walks you through connecting Companyenrich to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Companyenrich agent that can enrich openai company profile by domain, find companies similar to stripe, search cybersecurity startups in berlin through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Companyenrich account through Composio's Companyenrich MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Companyenrich with - [OpenAI Agents SDK](https://composio.dev/toolkits/companyenrich/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/companyenrich/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/companyenrich/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/companyenrich/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/companyenrich/framework/codex) - [OpenClaw](https://composio.dev/toolkits/companyenrich/framework/openclaw) - [Hermes](https://composio.dev/toolkits/companyenrich/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/companyenrich/framework/cli) - [Google ADK](https://composio.dev/toolkits/companyenrich/framework/google-adk) - [LangChain](https://composio.dev/toolkits/companyenrich/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/companyenrich/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/companyenrich/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/companyenrich/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Companyenrich integration - Using Composio's Tool Router to dynamically load and access Companyenrich tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## What is the Companyenrich MCP server, and what's possible with it? The Companyenrich MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Companyenrich account. It provides structured and secure access so your agent can perform Companyenrich operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `COMPANYENRICH_AUTOCOMPLETE_COMPANIES` | Autocomplete Companies | Returns a list of companies matching the given partial domain name. This is useful for autocompleting domain names in your application. Up to 10 companies are returned per request. Cost: FREE - No credits deducted. Use when you need to autocomplete company domains in your application. | | `COMPANYENRICH_AUTOCOMPLETE_KEYWORDS` | Autocomplete Keywords | Lookup keywords for use in company search filters. This endpoint returns a list of keywords that match the provided query string. Use this action to discover valid keyword values before using them in company search filters. The results are sorted by relevance. Example: query="tech" might return ["Technology", "Tech", "Information Technology", ...] | | `COMPANYENRICH_AUTOCOMPLETE_POSITIONS` | Autocomplete Positions | Lookup positions/job titles for use in people search filters. This endpoint returns a list of job titles that match the provided query string. Use this action to discover valid position values before using them in people search filters. The results are sorted by relevance. Example: query="engineer" might return ["Software Engineer", "Data Engineer", "Sales Engineer", ...] | | `COMPANYENRICH_AUTOCOMPLETE_TECHNOLOGIES` | Autocomplete Technologies | Lookup technologies for use in company search filters. This endpoint returns a list of technology names that match the provided query string. Use this action to discover valid technology values before using them in company search filters. The results are sorted by relevance. Example: query="react" might return ["React", "React Native", "ReactJS", ...] | | `COMPANYENRICH_COUNT_COMPANIES` | Count companies matching search criteria | Returns the total count of companies matching the given search criteria without retrieving the actual results. Use this action to check how many companies match your filters before performing a full search. Cost: FREE - No credits deducted. | | `COMPANYENRICH_COUNT_SIMILAR_COMPANIES` | Count Similar Companies | Tool to count the total number of similar companies matching the given search criteria without retrieving the actual results. Use when you need to know how many similar companies exist before making a request to fetch them, or when you only need the count without the full company details. Cost: FREE - No credits deducted. | | `COMPANYENRICH_CREATE_PEOPLE_SEARCH_EXPORT_JOB` | Create people search export job | Creates an asynchronous search export job for up to 50,000 people. Use when you need to export large sets of people data that will be processed in the background. The job returns immediately with a job ID, and the webhook URL will be called with a notification when processing completes. Cost: 2 credits per person returned (charged on completion). | | `COMPANYENRICH_CREATE_SEARCH_EXPORT_JOB` | Create search export job | Creates an asynchronous search export job for company data. Supports both standard company search and similar-company search. Returns a job ID immediately while processing happens in the background. The webhook URL (if provided) will be called with a notification when processing completes. Cost: 1 credit per company returned (charged on completion). Use this action when you need to export large datasets (up to 50,000 companies) that would take too long for a synchronous request. The job runs asynchronously and notifies you via webhook when complete. | | `COMPANYENRICH_ENRICH_BY_DOMAIN` | Enrich company by domain | Enriches a company using its domain name as lookup parameter. This is the preferred way to enrich a company as domain lookups are fast and reliable. Each domain maps to a unique company. Cost: 1 credit per call (5 credits if workforce expansion is requested). | | `COMPANYENRICH_ENRICH_BY_PROPERTIES` | Enrich company by properties | Enriches a company using its properties. You must provide at least one of the following properties: name, linkedinUrl, linkedinId, twitterUrl, facebookUrl, instagramUrl. Best match is used to determine the company in case of ambiguity. Cost: 1 credit per call (5 credits if workforce expansion is requested). | | `COMPANYENRICH_ENRICH_COMPANIES` | Batch Enrich Companies | Enriches a list of companies using their domain names. Use when you need to enrich multiple companies in a single request. Up to 50 domains can be provided. Each domain maps to a unique company. Cost: 1 credit per domain enriched (5 credits for workforce expansion). | | `COMPANYENRICH_FIND_SIMILAR_COMPANIES` | Find Similar Companies | Tool to find similar companies to the given company by domain. Use when you need to find companies similar to a target company based on industry, size, or other characteristics. Returns up to 100 companies per request. Cost: 5 credits per company returned, 5 credits if no results found. | | `COMPANYENRICH_GET_BULK_ENRICHMENT_JOB_STATUS` | Get Bulk Enrichment Job Status | Returns the current status of a bulk enrichment job. Once the job is completed, the response includes a results_url to download the enrichment results. Cost: FREE - No credits deducted. Use when you need to check the progress of a bulk enrichment job or get the results URL after the job completes. | | `COMPANYENRICH_GET_COMPANY_WORKFORCE` | Get Company Workforce | Returns workforce insights for a single company. You must provide exactly one lookup parameter: id or domain. The response includes observed employee count, an employee range bucket, and headcounts grouped by root departments. Costs 5 credits per successful call. Use when you need to find workforce details (employee count, department breakdown) for a specific company given its domain or company ID. | | `COMPANYENRICH_GET_COUNTRY_BY_CODE` | Get Country by Code | Tool to search for a country by its ISO 3166-1 alpha-2 code. Returns country information including name, coordinates, and country code. Use when you need to retrieve details about a specific country. Example: Get country details for US, GB, DE, etc. | | `COMPANYENRICH_GET_CURRENT_USER` | Get Current User | Returns information about the authenticated user, including their API key, credit balance, and account capabilities. This endpoint requires authentication via an API key in the Authorization header. Cost: FREE - No credits deducted. | | `COMPANYENRICH_GET_JOB_DETAILS` | Get Job Details | Returns details for a specific job by ID. Use when you need to check the status, progress, or result of an async enrichment job. Cost: FREE - No credits deducted. | | `COMPANYENRICH_GET_PEOPLE_SEARCH_EXPORT_JOB_STATUS` | Get People Search Export Job Status | Returns the current status of a person search export job. Once completed, includes the results_url to download the export results. Use when: - Checking if an async person search export job has completed - Getting the download URL for completed exports - Monitoring job progress or checking for errors Cost: FREE - No credits deducted for status checks. | | `COMPANYENRICH_GET_REGIONS` | Get Regions | Tool to get all available regions. Returns a list of all geographic regions supported by the API. Use when you need to retrieve region information for filtering or validation purposes. | | `COMPANYENRICH_GET_SEARCH_EXPORT_JOB_STATUS` | Get search export job status | Returns the current status of a search export job. Once the job is completed, the response will include a results_url that can be used to download the exported company data. This action is free - no credits are deducted. Use this action to: - Check if an export job has completed - Get the download URL for completed exports - Monitor job progress and troubleshoot failures | | `COMPANYENRICH_LIST_ALL_JOBS` | List all jobs | Returns a paginated list of all jobs (bulk enrichment, etc.) for the authenticated user. Supports optional filtering by job status and type. Cost: FREE - No credits deducted. Use this action to: - View all your jobs - Check the status of jobs - Monitor job progress and completion - Filter jobs by status (pending, processing, completed, failed, etc.) - Filter jobs by type (bulk_enrichment, etc.) | | `COMPANYENRICH_LIST_BULK_ENRICHMENT_JOBS` | List bulk enrichment jobs | Returns a paginated list of all bulk enrichment jobs for the authenticated user. Supports optional filtering by job status. This action is free - no credits are deducted. Use this action to: - View all your bulk enrichment jobs - Check the status of enrichment jobs - Monitor enrichment job progress and completion - Filter jobs by status (pending, processing, completing, completed, failed) | | `COMPANYENRICH_LIST_INDUSTRIES` | List Industries | Obtain a list of all company industries. Returns all industry names along with their associated NAICS code prefixes. Use when you need to retrieve the complete list of industries for filtering or categorization. | | `COMPANYENRICH_LIST_PEOPLE_SEARCH_EXPORT_JOBS` | List Person Search Export Jobs | Returns a paginated list of all person search export jobs for the authenticated user. Supports optional filtering by job status. Use this to check the status of previously submitted export jobs, view progress, or retrieve export results. Cost: FREE - No credits deducted. | | `COMPANYENRICH_LIST_SEARCH_EXPORT_JOBS` | List search export jobs | Returns a paginated list of all search export jobs for the authenticated user. Supports optional filtering by job status. This action is free - no credits are deducted. Use this action to: - View all your search export jobs - Check the status of export jobs - Monitor export job progress and completion - Filter jobs by status (pending, processing, completed, failed, etc.) | | `COMPANYENRICH_LOOKUP_PERSON` | Lookup Person by Email | Look up a person by email address. We resolve the company from the email domain first, then match the person by email local-part patterns. Returns the best deterministic match when found. Costs 5 credits per successful call. Use when you need to find person details (name, position, company, etc.) given an email address. | | `COMPANYENRICH_SCROLL_PEOPLE_SEARCH` | Search people with cursor pagination | Searches people based on given criteria using cursor-based pagination. Use when you need to find people at specific companies or with particular roles. You can request the next page of results by using the cursor parameter. Cost: 2 credits per person returned, 2 credits minimum if no results are found. | | `COMPANYENRICH_SEARCH_CITIES` | Search cities by name or country | Search for cities by name or country codes. Returns up to 100 cities per page. Use when you need to find cities matching a query string, optionally filtered by country codes. | | `COMPANYENRICH_SEARCH_COMPANIES` | Search companies by criteria | Searches companies based on given criteria. You can search by name, domain, industry, employees, revenue, founded year, and more. Up to 10,000 results can be returned from this endpoint (page * pageSize cannot exceed 10,000). For more results, use the scroll endpoint. Cost: 1 credit per company returned, 1 credit minimum if no results are found. | | `COMPANYENRICH_SEARCH_COUNTRIES` | Search Countries | Tool to search countries by name. Returns up to 100 countries per page. Use when you need to find country information including codes, names, and coordinates. Supports pagination and filtering by name query. | | `COMPANYENRICH_SEARCH_PEOPLE` | Search People | Searches people based on given criteria using page-based pagination. Up to 10,000 results can be returned from this endpoint (page * pageSize cannot exceed 10,000). For more results, use the scroll endpoint. Cost: 2 credits per person returned, 2 credits minimum if no results are found. | | `COMPANYENRICH_SEARCH_STATES` | Search States | Tool to search states by name or country codes. Returns up to 100 states per page. Use when you need to find states within a country or search states by name. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Companyenrich MCP server is an implementation of the Model Context Protocol that connects your AI agent to Companyenrich. It provides structured and secure access so your agent can perform Companyenrich operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before you begin, make sure you have: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); ``` ### 5. Create Tool Router session and initialize MCP client What's happening: - We're creating a Tool Router session that gives your agent access to Companyenrich tools - The create method takes the user ID and specifies which toolkits should be available - The returned mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all Companyenrich-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["companyenrich"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available Companyenrich tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to companyenrich, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use Companyenrich tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Complete Code ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["companyenrich"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to companyenrich, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Companyenrich agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build Companyenrich MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/companyenrich/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/companyenrich/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/companyenrich/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/companyenrich/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/companyenrich/framework/codex) - [OpenClaw](https://composio.dev/toolkits/companyenrich/framework/openclaw) - [Hermes](https://composio.dev/toolkits/companyenrich/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/companyenrich/framework/cli) - [Google ADK](https://composio.dev/toolkits/companyenrich/framework/google-adk) - [LangChain](https://composio.dev/toolkits/companyenrich/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/companyenrich/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/companyenrich/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/companyenrich/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. 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Get detailed environmental insights directly from your own sensors for smarter apps and automations. - [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements. - [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints. - [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots. - [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches. - [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand. - [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance. - [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows. - [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses. - [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research. - [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction. - [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation. - [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Companyenrich MCP? With a standalone Companyenrich MCP server, the agents and LLMs can only access a fixed set of Companyenrich tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Companyenrich and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Companyenrich tools. ### Can I manage the permissions and scopes for Companyenrich while using Tool Router? Yes, absolutely. You can configure which Companyenrich scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do. ### How safe is my data with Composio Tool Router? All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Companyenrich data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)