How to Use the Codacy MCP in OpenAI Agents SDK

Q: Can OpenAI Agents SDK report Codacy grades?

Yes, you use the getrepositoryqualityanalysis tool. The agent retrieves the grade and processes it based on your defined safety constraints.

Use the Codacy MCP Server to push quality metrics directly into your OpenAI Agents SDK production pipeline.

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Connect Codacy MCP to OpenAI Agents SDK

Create your Vinkius account to connect Codacy 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 Codacy with OpenAI Agents SDK

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Monitor repository grades in OpenAI Agents SDK

Stop guessing if your code is clean. Call `get_repository_quality_analysis` to pull specific metrics into your OpenAI Agents SDK logic. Your agent checks the grade, then triggers a fix if the score drops below your threshold. It keeps your production codebase stable without manual intervention.

Search issues with OpenAI Agents SDK

Pipe technical debt directly into your agent's context. Run `search_repository_issues` to grab every violation found by the Codacy engine. You'll get a list of actionable items. Your agent reads these, sorts them by priority, and creates Jira tickets or pull request comments.

Audit team access in OpenAI Agents SDK

Keep your project permissions tight. Use `list_organization_members` to verify who has access to your repos within the OpenAI Agents SDK environment. Your agent flags unauthorized accounts instantly. It provides an automated audit trail for your security team to review on the OpenAI dashboard.

Setup guide

Set up Codacy 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 Codacy tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Codacy 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="Codacy Agent",
            instructions="You have access to Codacy tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Codacy MCP in OpenAI Agents SDK

Install the openai-agents package and define the MCPServerStreamableHttp endpoint. Your agent discovers the toolset automatically at runtime.

Yes, you use the `get_repository_quality_analysis` tool. The agent retrieves the grade and processes it based on your defined safety constraints.

It works perfectly. Every action triggered by the tool is captured in your OpenAI dashboard logs for full visibility.

No. Set cacheToolsList to True and the SDK handles everything. It maps the tools to your agent methods without boilerplate.

Codacy only processes analysis metrics and issue metadata. Your actual source code remains on your servers while this MCP Server handles the reporting layer.

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