How to Use the Mistral AI MCP in Google ADK

Q: How do I configure the Mistral AI MCP Server in Google ADK?

Install the package, define McpToolset with the streamable HTTP transport parameters, and pass it to your LlmAgent. Your Google ADK agent will immediately discover all ten Mistral AI tools including chatcompletion and listmodels.

Q: Can I restrict which Mistral AI tools are exposed to Google ADK?

Yes, you can use the optional toolnames filter in your McpToolset configuration. This restricts the Google ADK agent to specific tools like createembeddings, preventing it from calling unused endpoints.

Run Mistral AI reasoning tools inside your Google ADK pipelines with this secure MCP Server to process BigQuery datasets.

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Connect Mistral AI MCP to Google ADK

Create your Vinkius account to connect Mistral AI to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Mistral AI with Google ADK

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Run code analysis on Google ADK

The `explain_code` and `generate_code` tools give your Google ADK agent the ability to analyze complex legacy codebases stored in Google Cloud Storage. The Gemini-powered agent reads your files, feeds the logic to Mistral AI models, and writes the docs. Because Google ADK integrates directly with Google Cloud infrastructure, you can run this pipeline inside your existing IAM security boundaries. The agent uses long-context reasoning to parse entire directories while offloading specific code generation tasks to the European models.

Process BigQuery data using Mistral AI tools

The `extract_entities` and `analyze_sentiment` tools let your Google ADK agent process unstructured text directly from your BigQuery tables. The agent queries your database, extracts clean JSON schemas from customer emails, and writes the structured results back to Google Cloud. You filter the exposed tools using the `tool_names` parameter to keep your enterprise agent focused only on specific analytical tasks. This architecture prevents your Google ADK pipelines from calling unnecessary endpoints, reducing execution latency.

Localize cloud content with translation tools

This MCP Server exposes `translate_text` and `fix_grammar` to let your Google ADK system translate enterprise documents stored in Google Cloud. The agent cleans up spelling mistakes and translates corporate policies across multiple European languages. You initialize the connection using `McpToolset` with the Vinkius HTTP transport URL and pass it directly to your `LlmAgent`. This setup allows your Google ADK agents to use specialized translation models without leaving your secure cloud environment.

Setup guide

Set up Mistral AI MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Mistral AI tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Mistral AI_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Mistral AI tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mistral AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Mistral AI MCP in Google ADK

Install the package, define `McpToolset` with the streamable HTTP transport parameters, and pass it to your `LlmAgent`. Your Google ADK agent will immediately discover all ten Mistral AI tools including `chat_completion` and `list_models`.

Yes, your Google ADK agent can retrieve raw text from BigQuery and pass it to Mistral AI tools like `summarize_text` or `extract_entities`. This lets you analyze massive cloud databases using specialized reasoning models.

Google ADK passes your requests through the Vinkius gateway using a single endpoint token. This setup manages your Mistral AI credentials securely, keeping your API keys out of your Google Cloud environment.

Yes, you can use the optional `tool_names` filter in your `McpToolset` configuration. This restricts the Google ADK agent to specific tools like `create_embeddings`, preventing it from calling unused endpoints.

Yes, your BigQuery data and text queries are processed in an ephemeral V8 sandbox. The Google ADK agent transmits data securely through the Vinkius gateway, ensuring no database records are stored or used for training.

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