Mistral AI MCP Server for Windsurf 10 tools — connect in under 2 minutes
Windsurf brings agentic AI coding to a purpose-built IDE. Connect Mistral AI through the Vinkius and Cascade will auto-discover every tool — ask questions, generate code, and act on live data without leaving your editor.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
Vinkius Desktop App
The modern way to manage MCP Servers — no config files, no terminal commands. Install Mistral AI and 2,500+ MCP Servers from a single visual interface.




{
"mcpServers": {
"mistral-ai": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Mistral AI MCP Server
Connect your Mistral AI account to any AI agent and leverage European-built AI models through natural conversation.
Windsurf's Cascade agent chains multiple Mistral AI tool calls autonomously — query data, analyze results, and generate code in a single agentic session. Paste the Vinkius Edge URL, reload, and all 10 tools are immediately available. Real-time tool feedback appears inline, so you see API responses directly in your editor.
What you can do
- Model Discovery — List all available Mistral models with their IDs, capabilities and context windows
- Chat Completions — Send conversations to Mistral models (large, small, codestral, nemo) and receive responses with configurable parameters
- Embeddings — Generate vector embeddings for semantic search, similarity comparison and vector storage
- Content Moderation — Check text for harmful categories (violence, hate, sexual, self-harm) with safety scores
- File Management — List and delete uploaded files used for batch processing and document AI
- Batch Processing — Create, track and cancel batch jobs for cost-effective asynchronous processing
The Mistral AI MCP Server exposes 10 tools through the Vinkius. Connect it to Windsurf in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Mistral AI to Windsurf via MCP
Follow these steps to integrate the Mistral AI MCP Server with Windsurf.
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
Add the server
Paste the JSON configuration above into mcp_config.json
Save and reload
Windsurf will detect the new server automatically
Start using Mistral AI
Open Cascade and ask: "Using Mistral AI, help me..." — 10 tools available
Why Use Windsurf with the Mistral AI MCP Server
Windsurf provides unique advantages when paired with Mistral AI through the Model Context Protocol.
Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention
Purpose-built for agentic workflows — Cascade understands context across your entire codebase and integrates MCP tools natively
JSON-based configuration means zero code changes: paste a URL, reload, and all 10 tools are immediately available
Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts
Mistral AI + Windsurf Use Cases
Practical scenarios where Windsurf combined with the Mistral AI MCP Server delivers measurable value.
Automated code generation: ask Cascade to fetch data from Mistral AI and generate models, types, or handlers based on real API responses
Live debugging: query Mistral AI tools mid-session to inspect production data while debugging without leaving the editor
Documentation generation: pull schema information from Mistral AI and have Cascade generate comprehensive API docs automatically
Rapid prototyping: combine Mistral AI data with Cascade's code generation to scaffold entire features in minutes
Mistral AI MCP Tools for Windsurf (10)
These 10 tools become available when you connect Mistral AI to Windsurf via MCP:
cancel_batch
Provide the batch ID. This is useful if you submitted a large batch by mistake and want to stop further processing. Cancel a running batch job
chat
Requires the model ID (e.g. "mistral-large-latest", "mistral-small-latest", "codestral-latest") and messages array in JSON format. Each message must have a "role" ("user", "assistant" or "system") and "content" (text). Optionally set max_tokens, temperature (0-1), top_p (0-1) and tools array for function calling. Returns the assistant's response. Send a chat message to a Mistral model
create_batch
Requires the input file ID (containing JSONL requests) and the endpoint (e.g. "/v1/chat/completions"). Returns the batch with its ID for tracking. Use list_batches and get_batch to monitor progress. Create a batch processing job
delete_file
Provide the file ID from list_files. WARNING: this action is irreversible. Delete an uploaded file from Mistral
embeddings
Requires the model ID and text input (string or array of strings). Returns embedding vectors for each input text. Useful for semantic search, similarity comparison and vector database storage. Generate embeddings using Mistral
get_batch
Provide the batch ID. Get details for a specific batch job
list_batches
Each batch shows its ID, status (queued, running, succeeded, failed, cancelled), input/output file IDs and request counts. List batch processing jobs
list_files
Files are used for fine-tuning, batch processing and document AI. Each file shows its ID, filename, purpose, size and upload date. List files uploaded to Mistral
list_models
Each model returns its ID (e.g. "mistral-large-latest", "mistral-small-latest", "codestral-latest"), display name, capabilities and context window. Use this to discover which models are available and their IDs for use with the chat tool. List all available Mistral AI models
moderate
). Requires the input text (string or array). Returns safety scores for each category. Useful for content filtering and safety checks before processing user input. Moderate text content with Mistral
Example Prompts for Mistral AI in Windsurf
Ready-to-use prompts you can give your Windsurf agent to start working with Mistral AI immediately.
"Send a message to Mistral Large asking 'What is the capital of France?'"
"List all available Mistral models."
"Moderate this text: 'I want to learn about AI safety and content filtering.'"
Troubleshooting Mistral AI MCP Server with Windsurf
Common issues when connecting Mistral AI to Windsurf through the Vinkius, and how to resolve them.
Server not connecting
Mistral AI + Windsurf FAQ
Common questions about integrating Mistral AI MCP Server with Windsurf.
How does Windsurf discover MCP tools?
mcp_config.json file on startup and connects to each configured server via Streamable HTTP. Tools are listed in the MCP panel and available to Cascade automatically.Can Cascade chain multiple MCP tool calls?
Does Windsurf support multiple MCP servers?
mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.Connect Mistral AI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Mistral AI to Windsurf
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
