How to Use the Code Climate MCP in OpenAI Agents SDK

Monitor your repository health directly within the OpenAI Agents SDK for production-grade visibility.

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Connect Code Climate MCP to OpenAI Agents SDK

Create your Vinkius account to connect Code Climate to OpenAI Agents SDK 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 OpenAI Agents SDK

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Automate repository health checks in OpenAI Agents SDK

Your agent pulls real-time metrics using `get_repository_code_quality` to flag regressions before they hit production. It reads snapshots to determine if your latest commit meets internal standards. This MCP Server provides the data your agent needs to decide when to block a deployment. It connects directly to your existing workflow without manual intervention.

Audit test coverage with OpenAI Agents SDK

The agent runs `list_repository_test_reports` to verify that new features have sufficient coverage. It maps these results back to your CI pipeline to catch gaps. Stop guessing if your tests are enough. Your agent now has the raw numbers to enforce strict testing requirements across every branch.

Trace code issues through OpenAI Agents SDK

Use `list_snapshot_code_issues` to grab specific technical debt items from your latest build. Your agent parses these findings to suggest immediate refactoring steps. It turns abstract quality scores into actionable tickets. You get clear visibility into what needs fixing without leaving your development environment.

Setup guide

Set up Code Climate MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Code Climate tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Code Climate tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Code Climate tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Code Climate Agent",
            instructions="You have access to Code Climate tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 Code Climate. 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 Code Climate MCP in OpenAI Agents SDK

You instantiate the server via the agent constructor. It maps tools automatically so your agent can query repository health instantly.

Yes. Your agent evaluates the data returned from the server and flags issues based on your defined safety constraints.

All communication happens over encrypted channels. We only touch your repository metadata and analysis snapshots, keeping your actual source code private.

No. Just point the server at your endpoint and the SDK handles the rest.

We only process analysis snapshots and repository metadata. Your data never leaves our secure sandbox during evaluation.

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