How to integrate PredictLeads MCP with Claude Agent SDK

This guide walks you through connecting PredictLeads to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working PredictLeads agent that can discover companies, find similar companies, search technologies, and review company intelligence through natural language commands. This guide will help you understand how to give your Claude Agent SDK agent real control over a PredictLeads account through Composio's PredictLeads MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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PredictLeads is a company intelligence API for hiring, technology, funding, news, product, and connection data. Use it to spot growth signals and enrich sales, research, and market workflows with fresh company context.

9 Tools

Introduction

This guide walks you through connecting PredictLeads to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working PredictLeads agent that can discover companies, find similar companies, search technologies, and review company intelligence through natural language commands.

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

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

Also integrate PredictLeads with

OpenAI Agents SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

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

What is Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework for building AI agents powered by Claude. It provides a streamlined interface for creating agents with MCP tool support and conversation management.

Key features include:

  • Native MCP Support: Built-in support for Model Context Protocol servers
  • Permission Modes: Control tool execution permissions
  • Streaming Responses: Real-time response streaming for interactive applications
  • Context Manager: Clean async context management for sessions

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

The PredictLeads MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your PredictLeads account. It provides structured and secure access to company profiles, hiring activity, technology adoption, financing, news, products, and business connections, so your agent can discover companies, research growth signals, compare similar businesses, search technologies, and monitor followed companies on your behalf.

  • Target company discovery: Have your agent find companies that match specific firmographic criteria and gather extended profiles for sales research.
  • Company intelligence research: Direct your agent to retrieve company details and investigate hiring, technology detections, news, financing, regulatory filings, business connections, website changes, repositories, and products.
  • Growth signal discovery: Let the agent search across companies for job openings, technology adoption, news, financing, investor portfolio connections, products, and startup platform posts.
  • Market and competitor analysis: Instruct your agent to find businesses similar to a chosen company and search the tracked technology catalog by name.
  • Account and company monitoring: Have your agent review followed companies and check your PredictLeads subscription status, monthly credit quota, and credit usage.

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 Claude/Anthropic API Key
  • Primary know-how of Claude Agents SDK
  • A PredictLeads account
  • Some knowledge of Python
2

Getting API Keys for Claude/Anthropic and Composio

Claude/Anthropic API Key
  • Go to the Anthropic Console and create an API key. You'll need credits to use the models.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

npm install @anthropic-ai/claude-agent-sdk @composio/core dotenv

Install the Composio SDK and the Claude Agents SDK.

What's happening:

  • @composio/core provides Composio integration for Anthropic
  • @anthropic-ai/claude-agent-sdk is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID identifies the user for session management
  • ANTHROPIC_API_KEY authenticates with Anthropic/Claude
5

Import dependencies

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

dotenv.config();
What's happening:
  • We're importing all necessary libraries including the Claude Agent SDK and Composio
  • The dotenv.config() function loads environment variables from your .env file
  • This setup prepares the foundation for connecting Claude with PredictLeads functionality
6

Create a Composio instance and Tool Router session

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });

  // Create Tool Router session for PredictLeads
  const session = await composio.create(USER_ID, {
    toolkits: ['predict_leads'],
  });
  const mcpUrl = session?.mcp.url;
What's happening:
  • The function checks for the required COMPOSIO_API_KEY environment variable
  • We're creating a Composio instance using our API key
  • The create method creates a Tool Router session for PredictLeads
  • The returned url is the MCP server URL that your agent will use
7

Configure Claude Agent with MCP

const options: Options = {
  permissionMode: 'bypassPermissions',
  mcpServers: {
    composio: {
      type: 'http',
      url: mcpUrl,
      headers: { 'x-api-key': COMPOSIO_API_KEY }
    }
  },
  systemPrompt: 'You are a helpful assistant with access to PredictLeads tools via Composio.',
  maxTurns: 10,
};
What's happening:
  • We're configuring the Claude Agent options with the MCP server URL
  • permissionMode: 'bypassPermissions' allows the agent to execute operations without asking for permission each time
  • The system prompt instructs the agent that it has access to PredictLeads
  • maxTurns: 10 limits the conversation length to prevent excessive API usage
8

Create client and start chat loop

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

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}
What's happening:
  • The readline interface is created to handle user input and output
  • The query function is used to send the user's input to the agent
  • The chat loop continues until the user types 'exit' or 'quit'
9

Run the application

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}
What's happening:
  • The chat function is the entry point for the application
  • The try-catch block is used to handle any errors that occur

Complete Code

Here's the complete code to get you started with PredictLeads and Claude Agent SDK:

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });
  const session = await composio.create(USER_ID, {
    toolkits: ['predict_leads']
  });
  const mcp_url = session?.mcp.url;

  const options: Options = {
    permissionMode: 'bypassPermissions',
    mcpServers: {
      composio: {
        type: 'http',
        url: mcp_url,
        headers: { 'x-api-key': COMPOSIO_API_KEY }
      }
    },
    systemPrompt: 'You are a helpful assistant with access to PredictLeads tools via Composio.',
    maxTurns: 10,
  };

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

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}

Conclusion

You've successfully built a Claude Agent SDK agent that can interact with PredictLeads through Composio's Tool Router.

Key features:

  • Native MCP support through Claude's agent framework
  • Streaming responses for real-time interaction
  • Permission bypass for smooth automated workflows
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
TOOLS

Supported Tools

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

Discover Companies

Find companies using firmographic filters.

Discover Intelligence

Discover one page of jobs, technology adoption, news, financing, investor portfolio connections, products, or startup-platform posts across companies.

Get API Subscription

Check PredictLeads subscription status, monthly credit quota, and credits used.

Get Company

Retrieve one company by PredictLeads UUID or bare domain.

Get Company Intelligence

Retrieve one page of a company's jobs, technology detections, news, financing, SEC filings, connections, website changes, GitHub repositories, or products.

Get Intelligence Record

Retrieve one job opening, extended technology detection, technology, news event, SEC filing, or product by identifier.

Get Similar Companies

Find one page of companies similar to a specified PredictLeads company UUID or domain.

List Followed Companies

List one page of companies already followed for PredictLeads webhook updates.

Search Technologies

Search PredictLeads' tracked technology catalog by fuzzy name.

FRAMEWORKS

How to build PredictLeads MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use PredictLeads MCP with OpenAI Agents SDK

Claude Code logo

Claude Code

Use PredictLeads MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use PredictLeads MCP with Claude Cowork

Codex logo

Codex

Use PredictLeads MCP with Codex

OpenClaw logo

OpenClaw

Use PredictLeads MCP with OpenClaw

Hermes logo

Hermes

Use PredictLeads MCP with Hermes

CLI logo

CLI

Use PredictLeads MCP with CLI

Google ADK logo

Google ADK

Use PredictLeads MCP with Google ADK

LangChain logo

LangChain

Use PredictLeads MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use PredictLeads MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use PredictLeads MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use PredictLeads MCP with LlamaIndex

CrewAI logo

CrewAI

Use PredictLeads MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, you can. Claude Agent 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 PredictLeads tools.

Yes, absolutely. You can configure which PredictLeads 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 PredictLeads data and credentials are handled as safely as possible.

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