Mistral AI MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Mistral AI through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token — get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Mistral AI, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* 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.
The Vercel AI SDK gives every Mistral AI tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
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 Vercel AI SDK 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 Vercel AI SDK via MCP
Follow these steps to integrate the Mistral AI MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from Mistral AI and passes them to the LLM
Why Use Vercel AI SDK with the Mistral AI MCP Server
Vercel AI SDK provides unique advantages when paired with Mistral AI through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime — same Mistral AI integration everywhere
Built-in streaming UI primitives let you display Mistral AI tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Mistral AI + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Mistral AI MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Mistral AI in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Mistral AI tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Mistral AI capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Mistral AI through natural language queries
Mistral AI MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Mistral AI to Vercel AI SDK 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 Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK 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 Vercel AI SDK
Common issues when connecting Mistral AI to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpMistral AI + Vercel AI SDK FAQ
Common questions about integrating Mistral AI MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Mistral AI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
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 Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.