How to integrate Peopledatalabs MCP with Mastra AI

Connect Mastra AI to Peopledatalabs MCP. Enrich this email with full person profile, standardize and clean this company name, and more using natural language, with authentication handled for you.

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Peopledatalabs

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Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.

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Introduction

This guide walks you through connecting Peopledatalabs to Mastra AI using the Composio tool router. By the end, you'll have a working Peopledatalabs agent that can enrich this email with full person profile, standardize and clean this company name, get detailed info for the skill 'python' through natural language commands.

This guide will help you understand how to give your Mastra AI agent real control over a Peopledatalabs account through Composio's Peopledatalabs MCP server.

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

Also integrate Peopledatalabs with

Claude Code Claude Cowork OpenAI Agents SDK Claude Agent SDK Grok Bot Muse Codex OpenClaw Hermes Atomic Agent Google ADK LangChain Vercel AI SDK LlamaIndex CrewAI Pydantic AI AutoGen

TL;DR

Here's what you'll learn:

Set up your environment so Mastra, OpenAI, and Composio work together
Create a Tool Router session in Composio that exposes Peopledatalabs tools
Connect Mastra's MCP client to the Composio generated MCP URL
Fetch Peopledatalabs tool definitions and attach them as a toolset
Build a Mastra agent that can reason, call tools, and return structured results
Run an interactive CLI where you can chat with your Peopledatalabs agent

What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.

Key features include:

MCP Client: Built-in support for Model Context Protocol servers
Toolsets: Organize tools into logical groups
Step Callbacks: Monitor and debug agent execution
OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

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

The People Data Labs MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your People Data Labs account. It provides structured and secure access to company records, job postings, data cleaning tools, and dataset schemas, so your agent can search companies, find job postings, standardize company and location data, suggest field values, and inspect available data fields on your behalf.

Company record search: Have your agent find companies that match specific criteria using flexible business data queries.
Company data cleanup: Let the agent standardize company details from a business name, website, or profile URL.
Location standardization: Direct your agent to turn raw location text into clean, structured geographic information.
Job posting discovery: Instruct your agent to search People Data Labs job postings using criteria relevant to your recruiting or market research.
Schema and field guidance: Have your agent inspect person or company data fields, review allowed values, and suggest completions for partial company, skill, or title text.

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:

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

Step-by-step Guide

Step by step09 STEPS

Prerequisites

Before starting, make sure you have:

Node.js 18 or higher
A Composio account with an active API key
An OpenAI API key
Basic familiarity with TypeScript

Getting API Keys for OpenAI and Composio

OpenAI API Key

Go to the OpenAI dashboard and create an API key.
You need credits or a connected billing setup to use the models.
Store the key somewhere safe.

Composio API Key

Log in to the Composio dashboard.
Go to Settings and copy your API key.
This key lets your Mastra agent talk to Composio and reach Peopledatalabs through MCP.

Install dependencies

bash

npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai dotenv

Install the required packages.

What's happening:

@composio/core is the Composio SDK for creating MCP sessions
@mastra/core provides the Agent class
@mastra/mcp is Mastra's MCP client
@ai-sdk/openai is the model wrapper for OpenAI
dotenv loads environment variables from .env

Set up environment variables

bash

COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

COMPOSIO_API_KEY authenticates your requests to Composio
COMPOSIO_USER_ID tells Composio which user this session belongs to
OPENAI_API_KEY lets the Mastra agent call OpenAI models

Import libraries and validate environment

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) 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 as string,
});

What's happening:

dotenv/config auto loads your .env so process.env.* is available
openai gives you a Mastra compatible model wrapper
Agent is the Mastra agent that will call tools and produce answers
MCPClient connects Mastra to your Composio MCP server
Composio is used to create a Tool Router session

Create a Tool Router session for Peopledatalabs

typescript

async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["peopledatalabs"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Peopledatalabs MCP URL:", composioMCPUrl);

What's happening:

create spins up a short-lived MCP HTTP endpoint for this user
The toolkits array contains "peopledatalabs" for Peopledatalabs access
session.mcp.url is the MCP URL that Mastra's MCPClient will connect to

Configure Mastra MCP client and fetch tools

typescript

const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);

What's happening:

MCPClient takes an id for this client and a list of MCP servers
The headers property includes the x-api-key for authentication
getTools fetches the tool definitions exposed by the Peopledatalabs toolkit

Create the Mastra agent

typescript

const agent = new Agent({
    name: "peopledatalabs-mastra-agent",
    instructions: "You are an AI agent with Peopledatalabs tools via Composio.",
    model: "openai/gpt-5",
  });

What's happening:

Agent is the core Mastra agent
name is just an identifier for logging and debugging
instructions guide the agent to use tools instead of only answering in natural language
model uses openai("gpt-5") to configure the underlying LLM

Set up interactive chat interface

typescript

let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\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({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        peopledatalabs: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    process.exit(0);
  });
}

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

What's happening:

messages keeps the full conversation history in Mastra's expected format
agent.generate runs the agent with conversation history and Peopledatalabs toolsets
maxSteps limits how many tool calls the agent can take in a single run
onStepFinish is a hook that prints intermediate steps for debugging

Complete Code

Here's the complete code to get you started with Peopledatalabs and Mastra AI:

typescript

import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) 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 as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["peopledatalabs"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      peopledatalabs: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "peopledatalabs-mastra-agent",
    instructions: "You are an AI agent with Peopledatalabs tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

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

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { peopledatalabs: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();

Conclusion

You've built a Mastra AI agent that can interact with Peopledatalabs through Composio's Tool Router. You can extend this further by:

Adding other toolkits like Gmail, Slack, or GitHub
Building a web-based chat interface around this agent
Using multiple MCP endpoints to enable cross-app workflows

TOOLS

Supported Tools

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

Bulk Retrieve Persons

Retrieve up to 100 People Data Labs person records by persistent ID.

Clean company data

Cleans and standardizes company information based on a name, website, or profile URL; providing at least one of these inputs is highly recommended for meaningful results.

Clean company data (POST)

Tool to clean and standardize company data using POST method.

Clean location data

Cleans and standardizes a raw, unformatted location string into a structured representation, provided the input is a recognizable geographical place.

Clean location data (POST)

Tool to clean and standardize location data using POST method.

Clean school data

Cleans and standardizes school information; provide at least one of the school's name, website, or profile for optimal results.

Clean school data (POST)

Tool to clean and standardize school data using POST method.

Enrich Bulk Company Data

Tool to enrich up to 100 companies in a single request using the Bulk Company Enrichment API.

Enrich bulk person data

Tool to enrich up to 100 person profiles in a single API request using the Bulk Person Enrichment API.

Enrich Company Data

Enriches company data from People Data Labs with details like firmographics and employee counts.

Enrich IP Data

Enriches an IP address with company, location, metadata, and person data from People Data Labs.

Enrich job title data

Enhances a job title by providing additional contextual information and details.

Enrich person data

Enriches person data using various identifiers; requires a primary ID (profile, email, phone, email_hash, lid, pdl_id) OR a name (full, or first and last) combined with another demographic detail (e.

Enrich skill data

Retrieves detailed, standardized information for a given skill by querying the People Data Labs Skill Enrichment API; for best results, provide a recognized professional skill or area of expertise.

Autocomplete field suggestions

Provides autocompletion suggestions for a specific field (e.

Get autocomplete suggestions (POST)

Tool to get autocompletion suggestions using POST method for complex query parameters.

Get column details

Retrieves predefined enum values for a column name from `enum_mappings.

Get schema

Retrieves the schema, including field names, descriptions, and data types, for 'person' or 'company' entity types.

Get subject requests

Tool to retrieve subject access requests for data privacy compliance.

Identify person data

Retrieves detailed profile information for an individual from People Data Labs (PDL), requiring at least one identifier such as email, phone, or profile URL.

People Search with Elasticsearch

Searches for person profiles in the People Data Labs (PDL) database using an Elasticsearch Domain Specific Language (DSL) query.

Query person changelog

Tool to query the changelog of person records between two consecutive dataset versions.

Retrieve person

Retrieve one person deterministically by persistent People Data Labs ID.

Company Search with Elasticsearch

Performs a search for company profiles within People Data Labs using a custom Elasticsearch Domain Specific Language (DSL) query.

Search Company Records (POST)

Tool to search and filter company records from the full Company Dataset using Elasticsearch or SQL queries via POST method.

Search job postings

Search PDL's Job Posting Dataset using one filter mode and cursor pagination.

FRAMEWORKS

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Grok Bot

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Muse

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Codex

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OpenClaw

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Hermes

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Atomic Agent

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Google ADK

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LangChain

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Vercel AI SDK

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LlamaIndex

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CrewAI

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Pydantic AI

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AutoGen

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MORE TOOLKITS

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Toolkit marketplace

Firecrawl

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Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.

Tavily

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Tavily offers powerful search and data retrieval from documents, databases, and the web. It helps teams locate and filter information instantly, saving hours on research.

Exa

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Exa is a data extraction and search platform for gathering and analyzing information from websites, APIs, or databases. It helps teams quickly surface insights and automate data-driven workflows.

Serpapi

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SerpApi is a real-time API for structured search engine results. It lets you automate SERP data collection, parsing, and analysis for SEO and research.

FAQ

Frequently asked questions

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

Yes, you can. Mastra AI 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 Peopledatalabs tools.

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

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How to integrate Peopledatalabs MCP with Mastra AI

Connect Peopledatalabs without auth hassles

Introduction

Also integrate Peopledatalabs with

TL;DR

What is Mastra AI?

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

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

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import libraries and validate environment

Create a Tool Router session for Peopledatalabs

Configure Mastra MCP client and fetch tools

Create the Mastra agent

Set up interactive chat interface

Complete Code

Conclusion

Supported Tools

How to build Peopledatalabs MCP Agent with another framework

Claude Code

Claude Cowork

OpenAI Agents SDK

Claude Agent SDK

Grok Bot

Muse

Codex

OpenClaw

Hermes

Atomic Agent

Google ADK

LangChain

Vercel AI SDK

LlamaIndex

CrewAI

Pydantic AI

AutoGen

Explore Other Toolkits

Firecrawl

Tavily

Exa

Serpapi

Frequently asked questions

What are the differences in Tool Router MCP and Peopledatalabs MCP?+

Can I use Tool Router MCP with Mastra AI?+

Can I manage the permissions and scopes for Peopledatalabs while using Tool Router?+

How safe is my data with Composio Tool Router?+

Start with Peopledatalabs.It takes 30 seconds.