How to integrate Mistral ai MCP with Mastra AI

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Introduction

This guide walks you through connecting Mistral ai to Mastra AI using the Composio tool router. By the end, you'll have a working Mistral ai agent that can summarize this research paper in simple terms, generate python code for sorting a list, explain the difference between ai and ml through natural language commands.

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

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

Also integrate Mistral ai with

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 Mistral ai tools
  • Connect Mastra's MCP client to the Composio generated MCP URL
  • Fetch Mistral ai 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 Mistral ai 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 Mistral ai MCP server, and what's possible with it?

The Mistral ai MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Mistral ai account. It provides structured and secure access to your Mistral AI models, so your agent can perform actions like generating text, summarizing content, answering questions, extracting structured information, and handling advanced language tasks on your behalf.

  • Text generation and completion: Have your agent produce coherent, context-aware text responses, complete prompts, or generate creative content leveraging Mistral's advanced models.
  • Summarization and paraphrasing: Ask your agent to summarize lengthy documents or rephrase input text for improved clarity or brevity.
  • Question answering and information extraction: Let your agent answer questions, extract key facts, or pull structured data from unstructured content automatically.
  • Content classification and sentiment analysis: Enable your agent to categorize text, detect topics, or analyze sentiment to inform downstream workflows.
  • Conversational AI and dialogue management: Build rich, multi-turn conversations or chatbots that handle context, intent, and user queries seamlessly using Mistral's models.

Supported Tools & Triggers

Tools
Append to conversationTool to append new entries to an existing conversation in Mistral AI.
Create AgentTool to create a new AI agent with custom configuration (Beta).
Create Agents CompletionTool to generate completions using a Mistral AI agent with specific instructions and tools.
Create Audio TranscriptionTranscribe audio files to text using Mistral AI's Voxtral models.
Create Chat CompletionGenerate conversational responses from Mistral AI models.
Create Chat ModerationTool to classify chat content for moderation purposes across 9 categories.
Create EmbeddingsTool to generate vector embeddings for input text using Mistral AI embedding models.
Create FIM CompletionGenerate code completions using fill-in-the-middle functionality.
Create libraryTool to create a new document library.
Create library shareCreate or update sharing permissions for a library.
Create ModerationTool to classify text content for moderation purposes across 9 categories.
Create OCRExtract text and structured data from images and documents using Mistral AI's OCR capabilities.
Create or Update Agent AliasTool to create or update an agent version alias.
Delete agentPermanently deletes an agent by its ID (Beta feature).
Delete ConversationTool to delete a conversation by its ID (Beta).
Delete FileDelete a file by its ID from Mistral AI.
Delete libraryPermanently deletes a library and all of its documents from Mistral AI.
Delete library documentPermanently deletes a document from a Mistral AI library.
Delete library shareRemove sharing permissions for a library from a user, workspace, or organization.
Download FileDownload the content of a previously uploaded file from Mistral AI.
Get AgentTool to retrieve details of a specific Mistral AI agent by its ID.
Get Agent VersionRetrieve a specific version of an agent (Beta).
Get ConversationTool to retrieve details of a specific conversation.
Get Conversation HistoryRetrieve the full history of a conversation in Mistral AI.
Get Conversation MessagesRetrieve all messages from a Mistral AI conversation.
Get document extracted text URLRetrieve a signed URL to download the extracted text from a document in a Mistral AI library.
Get document signed URLGet a signed URL to download a document from a Mistral AI library.
Get Document StatusRetrieve the processing status of a document in a Mistral AI library.
Get Document Text ContentRetrieve the extracted text content of a specific document from a Mistral AI library (Beta).
Get File Signed URLGet a time-limited signed URL for downloading a file from Mistral AI.
List Fine Tuning JobsList fine-tuning jobs with optional filtering and pagination.
Get libraryRetrieve detailed information about a specific library.
Get Library DocumentRetrieve metadata for a specific document in a Mistral AI library.
Get ModelTool to retrieve detailed information about a specific Mistral AI model by its ID.
List agent aliasesRetrieve all aliases for an agent version.
List AgentsTool to list all configured agents (Beta).
List Agent VersionsList all versions of a specific agent.
List Batch JobsTool to retrieve a list of all batch jobs with optional filtering and pagination.
List ConversationsList all created conversations (Beta).
List FilesTool to list all files available to the user.
List librariesList all document libraries accessible to your organization.
List Library DocumentsList all documents in a Mistral AI document library.
List library sharesList all sharing permissions for a document library.
List ModelsTool to retrieve all available Mistral AI models including base models and fine-tuned models.
Reprocess documentReprocess a document in a Mistral AI library (Beta).
Restart ConversationTool to restart a conversation from a specific point (Beta).
Retrieve FileRetrieve metadata of a file uploaded to Mistral AI.
Start ConversationTool to start a new conversation with a Mistral AI agent or base model.
Update AgentTool to update an existing agent's configuration.
Update agent versionTool to update the current version of an agent (Beta).
Update libraryTool to update an existing document library's properties.
Update library documentUpdate the metadata of a document in a Mistral AI library.
Upload FileUpload a file to Mistral AI for use in fine-tuning, batch processing, or OCR.
Upload Library DocumentUpload a document to a Mistral AI library for use with RAG-enabled agents.

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

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 Mistral ai 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 Mistral ai

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

  const composioMCPUrl = session.mcp.url;
  console.log("Mistral ai MCP URL:", composioMCPUrl);
What's happening:
  • create spins up a short-lived MCP HTTP endpoint for this user
  • The toolkits array contains "mistral_ai" for Mistral ai 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 Mistral ai toolkit

Create the Mastra agent

typescript
const agent = new Agent({
    name: "mistral_ai-mastra-agent",
    instructions: "You are an AI agent with Mistral ai 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: {
        mistral_ai: 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 Mistral ai 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 Mistral ai 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: ["mistral_ai"],
  });

  const composioMCPUrl = session.mcp.url;

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

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "mistral_ai-mastra-agent",
    instructions: "You are an AI agent with Mistral ai 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: { mistral_ai: 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 Mistral ai 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

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FAQ

What are the differences in Tool Router MCP and Mistral ai MCP?

With a standalone Mistral ai MCP server, the agents and LLMs can only access a fixed set of Mistral ai tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Mistral ai 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 Mistral ai tools.

Can I manage the permissions and scopes for Mistral ai while using Tool Router?

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

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