# How to integrate Datagma MCP with Mastra AI

```json
{
  "title": "How to integrate Datagma MCP with Mastra AI",
  "toolkit": "Datagma",
  "toolkit_slug": "datagma",
  "framework": "Mastra AI",
  "framework_slug": "mastra-ai",
  "url": "https://composio.dev/toolkits/datagma/framework/mastra-ai",
  "markdown_url": "https://composio.dev/toolkits/datagma/framework/mastra-ai.md",
  "updated_at": "2026-05-12T10:08:20.171Z"
}
```

## Introduction

This guide walks you through connecting Datagma to Mastra AI using the Composio tool router. By the end, you'll have a working Datagma agent that can identify top competitors in your industry, find recent market trends for saas, analyze growth opportunities in fintech through natural language commands.
This guide will help you understand how to give your Mastra AI agent real control over a Datagma account through Composio's Datagma MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Datagma with

- [OpenAI Agents SDK](https://composio.dev/toolkits/datagma/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/datagma/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/datagma/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/datagma/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/datagma/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/datagma/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/datagma/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/datagma/framework/cli)
- [Google ADK](https://composio.dev/toolkits/datagma/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/datagma/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/datagma/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/datagma/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/datagma/framework/crew-ai)

## 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 Datagma tools
- Connect Mastra's MCP client to the Composio generated MCP URL
- Fetch Datagma 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 Datagma 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 Datagma MCP server, and what's possible with it?

The Datagma MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Datagma account. It provides structured and secure access to your Datagma data intelligence platform, so your agent can perform actions like uncovering market insights, tracking competitor activities, analyzing industry trends, and supporting strategic growth decisions on your behalf.
- In-depth market insights extraction: Enable your agent to gather and analyze real-time market data to identify emerging opportunities and potential threats.
- Competitor metrics tracking: Let your agent monitor competitor performance, product launches, and strategic moves for sharper benchmarking.
- Growth opportunity identification: Task your agent with surfacing new business prospects and growth areas using Datagma's data intelligence resources.
- Customized analytics reporting: Have your agent generate tailored reports and dashboards that summarize key metrics and actionable insights.
- Trend and pattern analysis: Empower your agent to spot industry trends, shifts in customer behavior, and evolving market dynamics for proactive strategy planning.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DATAGMA_DETECT_JOB_CHANGE` | Detect Job Change | Tool to detect if a contact changed jobs. Use when verifying a contact’s current employment details by email. |
| `DATAGMA_ENRICH_PERSON_OR_COMPANY` | Enrich Person or Company | Enrich person or company data using LinkedIn URLs, emails, domains, or names. Returns enriched data including: contact information, LinkedIn profiles, company details, work experience, education, phone numbers (with phoneFull), and company metrics. Input types: LinkedIn profile URL (~100% success), email (~60% success), name+company (~90% success), company domain/name, or SIREN number (French companies). |
| `DATAGMA_FIND_WORK_EMAIL` | Find Work Email | Find verified work email address for a person using their name and company. Returns a professionally verified email address with validation metadata including SMTP checks and MX records. Requires either fullName or firstName+lastName, plus company domain or LinkedIn company slug. |
| `DATAGMA_GET_CREDITS` | Get Credits | Get the current credit balance for the authenticated Datagma API account. Use this to check how many API credits remain before making enrichment calls. |
| `DATAGMA_GET_TWITTER_BY_EMAIL` | Get Twitter Profile By Email | Retrieve Twitter account information associated with an email address. This action looks up Twitter username and display name for a given email address using Datagma's enrichment database. Returns Twitter username, display name, and the queried email if a match is found, or status 'NOT_FOUND' if no Twitter account is associated with the email. Use this when you need to: - Find someone's Twitter handle from their email address - Verify if an email has an associated Twitter account - Enrich contact data with social media information |
| `DATAGMA_GET_TWITTER_BY_USERNAME` | Get Twitter Profile by Username | Enrich Twitter profile data using Datagma's database. Returns contact information (email), social media profiles (LinkedIn, Facebook, GitHub), and professional details (skills, interests, industry) associated with a Twitter username. Note: Not all usernames are in Datagma's database. A 'not found' response (code 5) indicates the username hasn't been indexed yet. |
| `DATAGMA_REVERSE_PHONE_LOOKUP` | Reverse Phone Lookup | Tool to reverse-lookup information associated with a phone number. Use when you have a phone number and need associated details (e.g., carrier, location). |
| `DATAGMA_SEARCH_PHONE_NUMBERS` | Search Phone Numbers | Find mobile phone numbers using email address and/or LinkedIn profile URL. Returns list of phone numbers with confidence scores and optional WhatsApp verification. Best results when both email and LinkedIn URL are provided. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Datagma MCP server is an implementation of the Model Context Protocol that connects your AI agent to Datagma. It provides structured and secure access so your agent can perform Datagma 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 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

### 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 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.
- This key lets your Mastra agent talk to Composio and reach Datagma through MCP.

### 2. Install dependencies

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

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import libraries and validate environment

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
```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,
});
```

### 5. Create a Tool Router session for Datagma

What's happening:
- create spins up a short-lived MCP HTTP endpoint for this user
- The toolkits array contains "datagma" for Datagma access
- session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
```typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["datagma"],
    },
  );

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

### 6. Configure Mastra MCP client and fetch tools

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 Datagma toolkit
```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);
```

### 7. Create the Mastra agent

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

### 8. Set up interactive chat interface

What's happening:
- messages keeps the full conversation history in Mastra's expected format
- agent.generate runs the agent with conversation history and Datagma 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
```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: {
        datagma: 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);
});
```

## Complete Code

```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: ["datagma"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "datagma-mastra-agent",
    instructions: "You are an AI agent with Datagma 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: { datagma: 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 Datagma 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

## How to build Datagma MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/datagma/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/datagma/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/datagma/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/datagma/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/datagma/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/datagma/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/datagma/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/datagma/framework/cli)
- [Google ADK](https://composio.dev/toolkits/datagma/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/datagma/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/datagma/framework/ai-sdk)
- [LlamaIndex](https://composio.dev/toolkits/datagma/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/datagma/framework/crew-ai)

## Related Toolkits

- [Firecrawl](https://composio.dev/toolkits/firecrawl) - Firecrawl automates large-scale web crawling and data extraction. It helps organizations efficiently gather, index, and analyze content from online sources.
- [Tavily](https://composio.dev/toolkits/tavily) - 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](https://composio.dev/toolkits/exa) - 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](https://composio.dev/toolkits/serpapi) - 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.
- [Peopledatalabs](https://composio.dev/toolkits/peopledatalabs) - Peopledatalabs delivers B2B data enrichment and identity resolution APIs. Supercharge your apps with accurate, up-to-date business and contact data.
- [Snowflake](https://composio.dev/toolkits/snowflake) - Snowflake is a cloud data warehouse built for elastic scaling, secure data sharing, and fast SQL analytics across major clouds.
- [Posthog](https://composio.dev/toolkits/posthog) - PostHog is an open-source analytics platform for tracking user interactions and product metrics. It helps teams refine features, analyze funnels, and reduce churn with actionable insights.
- [Amplitude](https://composio.dev/toolkits/amplitude) - Amplitude is a digital analytics platform for product and behavioral data insights. It helps teams analyze user journeys and make data-driven decisions quickly.
- [Bright Data MCP](https://composio.dev/toolkits/brightdata_mcp) - Bright Data MCP is an AI-powered web scraping and data collection platform. Instantly access public web data in real time with advanced scraping tools.
- [Browseai](https://composio.dev/toolkits/browseai) - Browseai is a web automation and data extraction platform that turns any website into an API. It's perfect for monitoring websites and retrieving structured data without manual scraping.
- [ClickHouse](https://composio.dev/toolkits/clickhouse) - ClickHouse is an open-source, column-oriented database for real-time analytics and big data processing using SQL. Its lightning-fast query performance makes it ideal for handling large datasets and delivering instant insights.
- [Coinmarketcal](https://composio.dev/toolkits/coinmarketcal) - CoinMarketCal is a community-powered crypto calendar for upcoming events, announcements, and releases. It helps traders track market-moving developments and stay ahead in the crypto space.
- [Control d](https://composio.dev/toolkits/control_d) - Control d is a customizable DNS filtering and traffic redirection platform. It helps you manage internet access, enforce policies, and monitor usage across devices and networks.
- [Databox](https://composio.dev/toolkits/databox) - Databox is a business analytics platform that connects your data from any tool and device. It helps you track KPIs, build dashboards, and discover actionable insights.
- [Databricks](https://composio.dev/toolkits/databricks) - Databricks is a unified analytics platform for big data and AI on the lakehouse architecture. It empowers data teams to collaborate, analyze, and build scalable solutions efficiently.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Dovetail](https://composio.dev/toolkits/dovetail) - Dovetail is a research analysis platform for transcript review and insight generation. It helps teams code interviews, analyze feedback, and create actionable research summaries.
- [Dub](https://composio.dev/toolkits/dub) - Dub is a short link management platform with analytics and API access. Use it to easily create, manage, and track branded short links for your business.
- [Elasticsearch](https://composio.dev/toolkits/elasticsearch) - Elasticsearch is a distributed, RESTful search and analytics engine for all types of data. It delivers fast, scalable search and powerful analytics across massive datasets.
- [Fireflies](https://composio.dev/toolkits/fireflies) - Fireflies.ai is an AI-powered meeting assistant that records, transcribes, and analyzes voice conversations. It helps teams capture call notes automatically and search or summarize meetings effortlessly.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Datagma MCP?

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

### Can I use Tool Router MCP with Mastra AI?

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 Datagma tools.

### Can I manage the permissions and scopes for Datagma while using Tool Router?

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)