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How to integrate Mistral ai MCP with Mastra AI

Connect Mastra AI to Mistral ai MCP. Summarize this research paper in simple terms, generate python code for sorting a list, and more using natural language, with authentication handled for you.

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Mistral ai is a research lab offering cutting-edge open-source language models and developer APIs. It empowers teams to add state-of-the-art natural language capabilities to any app or workflow.

105 Tools

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

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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.

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:
  • Node.js 18 or higher
  • A Composio account with an active API key
  • An OpenAI API key
  • Basic familiarity with TypeScript
2

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.
3

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
4

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
5

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
6

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
7

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
8

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
9

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
TOOLS

Supported Tools

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

Append to conversation

Tool to append new entries to an existing conversation in Mistral AI.

Archive Fine-Tuned Model

Archive a fine-tuned model so it is unavailable until restored.

Count Chat Completion Field Options

Count values of a chat completion field after optional filtering.

Create Agent

Tool to create a new AI agent with custom configuration (Beta).

Create Agents Completion

Tool to generate completions using a Mistral AI agent with specific instructions and tools.

Create Audio Transcription

Transcribe audio files to text using Mistral AI's Voxtral models.

Create Batch Job

Create and queue a Mistral batch inference job.

Create Chat Completion

Generate conversational responses from Mistral AI models.

Create Chat Moderation

Tool to classify chat content for moderation purposes across 9 categories.

Create Embeddings

Tool to generate vector embeddings for input text using Mistral AI embedding models.

Create FIM Completion

Generate code completions using fill-in-the-middle functionality.

Create library

Tool to create a new document library.

Create library share

Create or update sharing permissions for a library.

Create Moderation

Tool to classify text content for moderation purposes across 9 categories.

Create OCR

Extract text and structured data from images and documents using Mistral AI's OCR capabilities.

Create or Update Agent Alias

Tool to create or update an agent version alias.

Create Speech

Generate JSON-encoded speech audio from text without streaming.

Delete agent

Permanently deletes an agent by its ID (Beta feature).

Delete Conversation

Tool to delete a conversation by its ID (Beta).

Delete File

Delete a file by its ID from Mistral AI.

Delete library

Permanently deletes a library and all of its documents from Mistral AI.

Delete library document

Permanently deletes a document from a Mistral AI library.

Delete library share

Remove sharing permissions for a library from a user, workspace, or organization.

Download File

Download the content of a previously uploaded file from Mistral AI.

Get Agent

Tool to retrieve details of a specific Mistral AI agent by its ID.

Get Agent Version

Retrieve a specific version of an agent (Beta).

Get Batch Job

Get details and optionally inline results for a batch job.

Get campaign

Retrieve an observability campaign by its UUID.

Get campaign status

Return the execution status of an observability campaign.

Get Chat Completion Event

Retrieve one observability chat completion event by UUID.

Get Chat Completion Field Options

Get available values for a chat completion field and filter operator.

Get Connector

Get a connector by ID or name without requesting customer data or secrets.

Get Connector Authentication Methods

Get a connector's public authentication methods and required headers.

Get Conversation

Tool to retrieve details of a specific conversation.

Get Conversation History

Retrieve the full history of a conversation in Mistral AI.

Get Conversation Messages

Retrieve all messages from a Mistral AI conversation.

Get dataset

Retrieve an observability dataset by its UUID.

Get dataset import task

Retrieve the status and progress of one dataset import task.

Get dataset record

Retrieve a conversation record from an observability dataset.

Get document extracted text URL

Retrieve a signed URL to download the extracted text from a document in a Mistral AI library.

Get document signed URL

Get a signed URL to download a document from a Mistral AI library.

Get Document Status

Retrieve the processing status of a document in a Mistral AI library.

Get Document Text Content

Retrieve the extracted text content of a specific document from a Mistral AI library (Beta).

Get File Signed URL

Get a time-limited signed URL for downloading a file from Mistral AI.

List Fine Tuning Jobs

List fine-tuning jobs with optional filtering and pagination.

Get Judge

Retrieve a saved observability judge by UUID.

Get library

Retrieve detailed information about a specific library.

Get Library Document

Retrieve metadata for a specific document in a Mistral AI library.

Get Model

Tool to retrieve detailed information about a specific Mistral AI model by its ID.

Get Similar Chat Completion Events

Retrieve observability events similar to a specified event.

Get Voice

Get saved voice metadata without sample audio.

Get Voice Sample

Download a saved voice's sample as a WAV audio file.

Get Workflow

Retrieve a workflow definition and its active-worker status by name or ID.

Get Workflow Deployment

Retrieve a workflow deployment and its registered workers.

Get Workflow Execution

Retrieve the current state and result of a workflow execution.

Get Workflow Execution History

Retrieve the event history for a workflow execution.

Get Workflow Execution OpenTelemetry Trace

Retrieve raw OpenTelemetry trace data for a workflow execution.

Get Workflow Execution Trace Events

Retrieve trace events for a workflow execution.

Get Workflow Execution Trace Summary

Retrieve a hierarchical trace summary for a workflow execution.

Get Workflow Metrics

Retrieve aggregate execution, error, latency, and retry metrics for a workflow.

Get Workflow Registration

Retrieve one workflow registration and its worker availability.

Get Workflow Run

Retrieve a workflow run's status, timing, execution IDs, and result.

Get Workflow Run History

Retrieve the event history for a workflow run.

Judge Chat Completion Event

Evaluate one chat completion event with an inline judge definition.

Judge Conversation

Run a saved observability judge against a supplied conversation.

Judge dataset record

Evaluate one dataset record with a supplied non-durable judge definition.

List agent aliases

Retrieve all aliases for an agent version.

List Agents

Tool to list all configured agents (Beta).

List Agent Versions

List all versions of a specific agent.

List Batch Jobs

Tool to retrieve a list of all batch jobs with optional filtering and pagination.

List campaigns

List observability campaigns, optionally filtering them by a text query.

List campaign selected events

List chat-completion events selected by an observability campaign.

List Chat Completion Fields

List fields and operators available for observability event filtering.

List Connectors

List custom MCP connectors without returning connection secrets.

List Connector Tools

List tools exposed by an MCP connector.

List Conversations

List all created conversations (Beta).

List dataset import tasks

List import tasks associated with an observability dataset.

List dataset records

List conversation records stored in an observability dataset.

List datasets

List observability datasets, optionally filtering them by a text query.

List Files

Tool to list all files available to the user.

List Judges

List saved observability judges with filtering, search, and pagination.

List libraries

List all document libraries accessible to your organization.

List Library Documents

List all documents in a Mistral AI document library.

List library shares

List all sharing permissions for a document library.

List Models

Tool to retrieve all available Mistral AI models including base models and fine-tuned models.

List Voices

List saved voices without sample audio data.

List Workflow Deployments

List workflow worker deployments, optionally filtering to active deployments or a workflow.

List Workflow Events

List durable workflow lifecycle and task events with cursor pagination.

List Workflow Registrations

List workflow registrations with sharing, activity, archival, and cursor filters.

List Workflow Runs

List workflow runs with status, search, and cursor pagination filters.

List Workflow Schedules

List workflow schedules with timing, time zone, and execution policy details.

Query Workflow Execution

Invoke a read-only query handler on a running workflow execution.

Reprocess document

Reprocess a document in a Mistral AI library (Beta).

Restart Conversation

Tool to restart a conversation from a specific point (Beta).

Retrieve File

Retrieve metadata of a file uploaded to Mistral AI.

Search Chat Completion Events

Search observability chat completion events and return previews or only IDs.

Start Conversation

Tool to start a new conversation with a Mistral AI agent or base model.

Unarchive Fine-Tuned Model

Restore an archived fine-tuned model.

Update Agent

Tool to update an existing agent's configuration.

Update agent version

Tool to update the current version of an agent (Beta).

Update Fine-Tuned Model

Update the name or description of a fine-tuned model.

Update library

Tool to update an existing document library's properties.

Update library document

Update the metadata of a document in a Mistral AI library.

Upload File

Upload a file to Mistral AI for use in fine-tuning, batch processing, or OCR.

Upload Library Document

Upload a document to a Mistral AI library for use with RAG-enabled agents.

FRAMEWORKS

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Antigravity logo

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OpenAI Agents SDK logo

OpenAI Agents SDK

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Claude Agent SDK logo

Claude Agent SDK

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Codex logo

Codex

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Grok Build logo

Grok Build

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VS Code logo

VS Code

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OpenCode logo

OpenCode

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OpenClaw logo

OpenClaw

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Hermes logo

Hermes

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Atomic Agent logo

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Google ADK logo

Google ADK

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LangChain logo

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Vercel AI SDK logo

Vercel AI SDK

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LlamaIndex logo

LlamaIndex

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CrewAI logo

CrewAI

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Pydantic AI logo

Pydantic AI

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AutoGen logo

AutoGen

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FAQ

Frequently asked questions

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.

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.

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.

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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