How to integrate Crustdata MCP with OpenAI Agents SDK

This guide walks you through connecting Crustdata to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Crustdata agent that can find tech companies with recent funding milestones, enrich this lead's profile with latest data, list top decision makers in saas startups through natural language commands. This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Crustdata account through Composio's Crustdata MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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CrustData is an AI-powered data intelligence platform for real-time company and people data. It helps B2B sales teams, AI SDRs, and investors react to live business signals.

14 Tools

Introduction

This guide walks you through connecting Crustdata to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Crustdata agent that can find tech companies with recent funding milestones, enrich this lead's profile with latest data, list top decision makers in saas startups through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Crustdata account through Composio's Crustdata MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

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TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Crustdata
  • Configure an AI agent that can use Crustdata as a tool
  • Run a live chat session where you can ask the agent to perform Crustdata operations

What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

What is the Crustdata MCP server, and what's possible with it?

The Crustdata MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Crustdata account. It provides structured and secure access to real-time company and people intelligence, so your agent can perform actions like lead enrichment, market research, investor portfolio analysis, and workforce trend tracking on your behalf.

  • Comprehensive person and company enrichment: Instantly enrich leads or companies with up-to-date details for customer profiling, data verification, or targeted outreach.
  • Advanced decision maker filtering: Find and analyze decision makers across organizations using complex filters, titles, and segmentation for your sales or marketing efforts.
  • Investor portfolio and funding milestone analysis: Retrieve in-depth investor portfolio data, analyze funding milestones, and generate reports for investment research or deal sourcing.
  • Workforce and job market trend insights: Fetch headcount and job listing timeseries data to track organizational growth, hiring activity, or competitive shifts in specific industries.
  • Social and web activity monitoring: Collect and analyze LinkedIn posts and web traffic data for any company to assess engagement, sentiment, and digital footprint for market intelligence and outreach strategies.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Crustdata project
  • Some knowledge of Python or Typescript
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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
3

Install dependencies

npm install @composio/openai-agents @openai/agents dotenv

Install the Composio SDK and the OpenAI Agents SDK.

4

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

5

Import dependencies

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Crustdata.
6

Set up the Composio instance

dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
What's happening:
  • dotenv.config() loads your .env file so COMPOSIO_API_KEY and USER_ID are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.
7

Create a Tool Router session

// Create Tool Router session for Crustdata
const session = await composio.create(userId as string, {
  toolkits: ['crustdata'],
});
const mcpUrl = session.mcp.url;

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only crustdata.
  • The router checks the user's Crustdata connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Crustdata.
  • This approach keeps things lightweight and lets the agent request Crustdata tools only when needed during the conversation.
8

Configure the agent

// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Crustdata. Help users perform Crustdata operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Crustdata and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a hostedMcpTool that connects to the MCP server URL we created earlier.
  • The headers object includes the Composio API key for secure authentication with the MCP server.
  • requireApproval: 'never' means the agent can execute Crustdata operations without asking for permission each time, making interactions smoother.
9

Start chat loop and handle conversation

// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
What's happening:
  • The program prints a session URL that you visit to authorize Crustdata.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using run().
  • The responses are printed to the console.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Crustdata and OpenAI Agents SDK:

import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['crustdata'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Crustdata. Help users perform Crustdata operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});

Conclusion

This was a starter code for integrating Crustdata MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Crustdata.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
TOOLS

Supported Tools

Every Crustdata action and event your agent gets out of the box.

Enrich person screener

The screener_person_enrich endpoint enriches person data by providing additional information based on the given query.

Fetch headcount by facet timeseries

Retrieves headcount data as a timeseries with faceted analysis capabilities.

Fetch investor portfolio data

Retrieves comprehensive investor portfolio data from the Data Lab section of the CrustData API.

Filter decision makers data

Filters and retrieves decision maker data from the CrustData B2B SaaS integration platform based on complex criteria.

Post funding milestone timeseries data

The FundingMilestoneTimeseries endpoint retrieves time-series data related to funding milestones for companies.

Post headcount timeseries data

Retrieves filtered and sorted headcount timeseries data from the CrustData Data Lab.

Post job listings table data

This endpoint retrieves filtered and sorted job listings data for specified company tickers from a chosen dataset in the CrustData platform.

Post web traffic data

Retrieves filtered and sorted web traffic data from the CrustData platform.

Retrieve linkedin posts

Retrieves LinkedIn posts for a specified company using CrustData's screener functionality.

Screener company information

The GetCompanyScreener endpoint allows users to search and filter companies based on various criteria such as headcount, growth rate, funding, and more.

Screen metrics and filter conditions

The ScreenData endpoint enables advanced data screening and filtering on the CrustData platform.

Search companies with filters

The CompanySearch endpoint enables users to search and filter companies using the CrustData API.

Search for job id in screener

The screener_person_search endpoint allows users to search for persons associated with a specific job ID within the CrustData B2B SaaS integration platform.

Search linkedin posts by keyword

This endpoint enables searching for LinkedIn posts using a specific keyword.

FAQ

Frequently asked questions

With a standalone Crustdata MCP server, the agents and LLMs can only access a fixed set of Crustdata tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Crustdata and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. OpenAI Agents SDK 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 Crustdata tools.

Yes, absolutely. You can configure which Crustdata 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.

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 Crustdata data and credentials are handled as safely as possible.

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