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Mistral MCP

by Swih

Connects MCP clients to Mistral chat, document extraction, OCR, vision, transcription, workflows, and code completion.

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Install Mistral MCP

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "swih-mistral-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "mistral-mcp@1.0.0"
      ],
      "env": {
        "MISTRAL_API_KEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Install not yet sandbox-tested— the server itself is confirmed live (we called its tools/list endpoint). The stdio install command is a separate, ongoing check.

Overview

Swih/mistral-mcp MCP server exposes Mistral Cloud capabilities through MCP, including chat, OCR, vision, audio transcription, document extraction, workflows, and code completion. It supports stdio and Streamable HTTP transports, with profiles that control which tool families are available. Use it when an agent needs Mistral models for multilingual content, invoice or document processing, image understanding, speech transcription, or Codestral-based code completion. A Mistral API key, model access, and available quota are required.

Use cases

  • Extract typed fields from invoices and contracts
  • Transcribe audio with optional speaker segments
  • Analyze images and PDFs with Mistral vision and OCR
  • Complete or refactor code with Codestral
  • Run and monitor Mistral workflows

Key features

  • Mistral chat and structured responses
  • PDF and image OCR
  • Vision requests with URL or base64 images
  • Voxtral audio transcription
  • Codestral fill-in-the-middle completion
  • Profile-based tool selection

Tools8

What Mistral MCP lets your agent do. Expand a tool for its parameters.

Verified live~3.6k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

18/19 checks healthy over the last 78d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 10d ago via OSV.dev · mistral-mcp@1.0.0 (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars15Stargazers on the source repository.
npm downloads729Package downloads in the last 30 days.
Last commit28d agoMost recent push to the default branch.
Tools exposed8Callable tools this server registers over MCP.
Directory activity3 viewsConfig copies, upvotes, and views on AllMCPs.

How Mistral MCP works

What Swih/mistral-mcp MCP server does

Swih/mistral-mcp MCP server connects MCP clients to Mistral APIs for text generation, structured document extraction, OCR, image-aware chat, audio transcription, and fill-in-the-middle coding. The default core profile exposes six tools covering documents, chat, vision, transcription, and code completion. Other profiles provide workflow orchestration, broader document tools, administration features, or a smaller self-hosted set.

Document processing can accept text or Markdown, document URLs, base64 images, or uploaded file IDs. It supports invoice, contract, identity-document, generic, and automatic classification modes. Typed extraction returns readable content together with structured content, but schema validation checks response shape rather than factual correctness or accounting accuracy.

How it works

The server receives tool calls over MCP and forwards supported requests to Mistral Cloud or a compatible configured endpoint. Chat responses include assistant text and token usage. OCR returns per-page Markdown and may include tables, headers, footers, links, images, annotations, confidence scores, and dimensions. Voxtral transcription returns text and detected language, with optional speaker segments and timestamps.

Workflow calls can either wait for a result or return an execution identifier immediately. workflow_status checks progress, while workflow_interact can signal, query, or update a running execution. Chat does not stream; use the separate streaming chat capability where long-output progress is needed and the selected profile exposes it.

Setup and configuration

To run the Swih/mistral-mcp MCP server, use Node.js 20 or newer, npm, and a Mistral API key with access to the requested models and sufficient quota. A typical stdio configuration runs npx -y mistral-mcp@1.0.0 and passes MISTRAL_API_KEY, MISTRAL_DEFAULT_MODEL, and MISTRAL_MCP_PROFILE in the client environment.

MISTRAL_MCP_PROFILE defaults to core. Set it to metier-docs for the legacy document and orchestration set, workflows for workflow-related tools, admin for all implemented tool families, or self-hosted for compatible custom endpoints. full is a deprecated alias for admin. The server reads environment values supplied by the client and does not automatically load .env files.

Use --doctor to inspect the local profile and tool list without making API calls. The mistral://capabilities resource reports the active endpoint and omitted tool families, but neither check confirms account permissions or quota.

Tools and capabilities

Available capabilities include:

  • process_document for classification and schema-validated extraction.
  • mistral_chat for Mistral chat completions and structured response formats.
  • mistral_ocr for PDF and image OCR.
  • mistral_vision for text-plus-image requests using URLs or base64 data.
  • voxtral_transcribe for audio transcription and optional diarization.
  • codestral_fim for code completion between a prefix and suffix.
  • Workflow execution, status, and interaction tools in applicable profiles.

The broader profiles also cover capabilities such as Files, Batch, Conversations, Libraries, connectors, and search-index discovery where implemented by the selected profile.

Limitations and notes

Swih/mistral-mcp MCP server sends cloud extraction requests to Mistral even when hosted locally. Model availability and free quota depend on the Mistral account. OCR and file-based processing require the relevant API access and quota. Text document inputs must contain non-whitespace content and stay within 60,000 UTF-16 code units.

Review extracted fields against the source before using them operationally. The documented live test covered one synthetic invoice and does not establish general extraction accuracy. Image requests require a vision-capable model, and audio transcription supports the documented Voxtral models. Changing profiles requires restarting the server and refreshing the client's tool catalog.

Read the full README View source on GitHub

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Frequently Asked Questions about Mistral MCP

Swih/mistral-mcp is an MCP server that connects MCP clients to Mistral APIs for chat, OCR, vision, audio transcription, document extraction, workflows, and Codestral code completion. It supports stdio and Streamable HTTP transports, uses profiles to select tool groups, and requires a Mistral API key with access and quota.

Install it in an MCP client by configuring the stdio command `npx -y mistral-mcp@1.0.0` and supplying `MISTRAL_API_KEY`. Node.js 20 or newer and npm are required. Add a default model and profile if needed, then restart the client and refresh its tool catalog.

The required environment variable is `MISTRAL_API_KEY`. `MISTRAL_DEFAULT_MODEL` selects the default chat model, and `MISTRAL_MCP_PROFILE` selects the active tool profile; the profile defaults to `core`. Environment values must be supplied by the MCP client because the server does not load `.env` automatically.

Yes, Swih/mistral-mcp can be used with Cursor through its standard MCP server configuration. Configure the stdio command and environment variables in the client, then restart or refresh tool discovery. The provided setup documentation does not describe a Cursor-specific installation format.

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