How to Use the Code Climate MCP in Pydantic AI

Get type-safe code quality insights in Pydantic AI with this MCP Server.

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Connect Code Climate MCP to Pydantic AI

Create your Vinkius account to connect Code Climate to Pydantic AI 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 Code Climate with Pydantic AI

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Validate Code Climate data with Pydantic AI

Every response from `list_repository_snapshots` is checked against your Pydantic schemas. If the API returns unexpected fields, the agent catches it immediately. This prevents your agent from making decisions based on bad data. You get reliable, typed responses every time you call a tool.

Audit test coverage using Pydantic AI

Your agent calls `list_repository_test_reports` to get verified coverage percentages. The framework ensures the data structure matches your internal requirements. It removes the risk of runtime errors when your agent processes complex analysis data. You define the structure, and the agent enforces it.

Retrieve repositories in Pydantic AI

Use `list_codeclimate_repositories` to get a structured list of all your projects. Pydantic AI ensures the returned list is always valid. This makes it simple to iterate over your projects. You never have to worry about null values or missing keys when your agent performs its checks.

Setup guide

Set up Code Climate MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "code-climate-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Code Climate tools.",
)

result = await agent.run("List recent Code Climate transactions")
print(result.output)

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Common questions about Code Climate MCP in Pydantic AI

If the data doesn't match your schema, the agent throws a validation error. This prevents silent failures during your quality check process.

Yes. You define the schema for the report, and the agent populates it with data from the server.

The combination is highly dependable. You get strict type checking for every single tool call.

You get full access to all eight tools, including repository lists and specific issue tracking.

We only process analysis snapshots and repository metadata. Your sensitive information remains protected by strict schema validation.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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