How to Use the Codecov MCP in AutoGen

Q: How do AutoGen agents talk to Codecov?

The agents use the mcpservertools adapter to invoke functions. They treat these tools as capabilities they can debate and execute during the conversation.

Q: Can my AutoGen agents debate Codecov branch status?

Yes, by calling listrepositorybranches, your agents can compare the status of different branches. They will argue over which branch is the most stable for deployment.

Let your AutoGen agents debate test coverage by connecting them to Codecov.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Codecov MCP to AutoGen

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

GDPR Free for Subscribers

Setup Codecov with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Debate coverage metrics in AutoGen

Have one agent call `get_commit_coverage_totals` while another critiques the result. They negotiate whether a commit is ready to merge based on the hard numbers. This multi-agent loop forces a consensus on code quality. The agents challenge each other until they agree the coverage meets your internal standards.

Automate Codecov audits with AutoGen

Deploy a security agent that uses `list_coverage_flags` to ensure test requirements are met. It debates with a developer agent if a flag is missing from a new feature. Your system converges on a decision without you needing to intervene. The agents handle the back-and-forth until the repository setup is compliant.

Manage repos with AutoGen agents

Instruct your agents to use `list_codecov_repositories` to inventory your projects. They discuss which repos need more aggressive testing based on the current metrics. This creates a self-governing team of agents. They identify low-coverage projects and propose fixes through their internal debate process.

Setup guide

Set up Codecov MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Codecov tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Codecov_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Codecov data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Codecov_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Codecov data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Codecov. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Codecov now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Codecov MCP in AutoGen

The agents use the `mcp_server_tools` adapter to invoke functions. They treat these tools as capabilities they can debate and execute during the conversation.

Yes, by calling `list_repository_branches`, your agents can compare the status of different branches. They will argue over which branch is the most stable for deployment.

Your repository coverage reports are processed in an ephemeral sandbox. Only the agents in your current session see the data, and it is wiped afterward.

You pass the tool list into the AssistantAgent constructor. This gives your agents permission to use the tools during their multi-agent deliberations.

The agents are provided the tool schemas automatically via the adapter. They understand how to call `get_repository_coverage_details` correctly based on the provided definitions.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript