Mistral AI MCP Server for Google ADK 10 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Mistral AI as an MCP tool provider through the Vinkius and your ADK agents can call every tool with full schema introspection.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
StreamableHTTPConnectionParams,
)
# Your Vinkius token — get it at cloud.vinkius.com
mcp_tools = McpToolset(
connection_params=StreamableHTTPConnectionParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
)
)
agent = Agent(
model="gemini-2.5-pro",
name="mistral_ai_agent",
instruction=(
"You help users interact with Mistral AI "
"using 10 available tools."
),
tools=[mcp_tools],
)
* 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.
Google ADK natively supports Mistral AI as an MCP tool provider — declare the Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 10 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
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 Google ADK 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 Google ADK via MCP
Follow these steps to integrate the Mistral AI MCP Server with Google ADK.
Install Google ADK
Run pip install google-adk
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Create the agent
Save the code above and integrate into your ADK workflow
Explore tools
The agent will discover 10 tools from Mistral AI via MCP
Why Use Google ADK with the Mistral AI MCP Server
Google ADK provides unique advantages when paired with Mistral AI through the Model Context Protocol.
Google ADK natively supports MCP tool servers — declare a tool provider and the framework handles discovery, validation, and execution
Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Mistral AI
Production-ready features like session management, evaluation, and deployment come built-in — not bolted on
Seamless integration with Google Cloud services means you can combine Mistral AI tools with BigQuery, Vertex AI, and Cloud Functions
Mistral AI + Google ADK Use Cases
Practical scenarios where Google ADK combined with the Mistral AI MCP Server delivers measurable value.
Enterprise data agents: ADK agents query Mistral AI and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine Mistral AI tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query Mistral AI regularly and flag policy violations or configuration drift
Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Mistral AI
Mistral AI MCP Tools for Google ADK (10)
These 10 tools become available when you connect Mistral AI to Google ADK 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 Google ADK
Ready-to-use prompts you can give your Google ADK 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 Google ADK
Common issues when connecting Mistral AI to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkMistral AI + Google ADK FAQ
Common questions about integrating Mistral AI MCP Server with Google ADK.
How does Google ADK connect to MCP servers?
Can ADK agents use multiple MCP servers?
Which Gemini models work best with MCP tools?
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.
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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 Google ADK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.