How to Use the Codecov MCP in OpenAI Agents SDK

Track test coverage metrics directly in your OpenAI Agents SDK production flows with this Codecov MCP server.

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Connect Codecov MCP to OpenAI Agents SDK

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

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Monitor commit coverage in OpenAI Agents SDK

Your agent pulls real-time stats for specific SHAs using `get_commit_coverage_totals`. It skips the UI and grabs numbers straight from the API. You'll see exactly how your commits affect the codebase. The `list_repository_commits` tool provides a quick audit of recent status changes.

Map project health with OpenAI Agents SDK

Navigate your file tree coverage with `get_coverage_report_tree`. It turns complex reports into a structure your agent can actually read. This makes identifying untested files trivial. You can then use `list_coverage_flags` to see how specific test suites group your logic.

Automate repository management for OpenAI Agents SDK

Your agent maintains a list of active projects via `list_codecov_repositories`. It keeps track of every connected repo without manual input. Use `get_repository_coverage_details` when you need a deep dive into project health. It validates that your production guardrails have enough test coverage.

Setup guide

Set up Codecov 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 Codecov tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Codecov 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="Codecov Agent",
            instructions="You have access to Codecov 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 Codecov MCP in OpenAI Agents SDK

Register the server as an MCP toolset in your agent definition. Once connected, your agent calls the tools directly to pull coverage data.

Yes, define your agent logic to trigger these tools after every commit. It verifies coverage status before moving to the next task.

The tools operate on real API data. We recommend using the OpenAI dashboard for tracing these calls to ensure your agent behaves as expected.

The SDK receives structured JSON responses from the server. Your agent processes these results to make decisions about code quality.

This server only processes repository coverage reports and metadata. No source code content leaves your environment during these MCP requests.

Use it with your favorite AI tools

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