How to Use the Code Climate MCP in AutoGen

Q: How do I register Code Climate MCP tools with an AutoGen agent?

Install autogen-extmcp and use mcpservertools with your server URL. Pass the resulting tool list directly to your AssistantAgent constructor.

Let your AutoGen agents debate code quality issues and negotiate refactoring priorities using real Code Climate metrics.

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Connect Code Climate MCP to AutoGen

Create your Vinkius account to connect Code Climate 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.

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Setup Code Climate with AutoGen

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Debate quality metrics with AutoGen agents

The `get_repository_code_quality` tool feeds raw quality metrics into your multi-agent conversations. A QA agent can argue for refactoring based on a low grade, while a product agent balances the schedule. This MCP Server exposes real-time data so your agents don't rely on outdated assumptions. They pull live grades to resolve conflicts and make informed project decisions.

Automate snapshot analysis in multi-agent workflows

The `list_repository_snapshots` tool allows your release agent to check the latest build quality before deployment. It compares the current snapshot against historical baselines to detect regressions. If issues are found, the agent calls `get_snapshot_quality_details` to isolate the problem. A developer agent then receives a structured brief detailing exactly what needs fixing.

Triage code issues and assign fix ownership

The `list_snapshot_code_issues` tool extracts active technical debt items for your triage agents to review. They categorize issues by severity and estimate the effort required to resolve them. Your system uses `get_my_codeclimate_profile` to verify current API access and allocate tasks to the appropriate team members. This keeps your entire issue tracking workflow completely automated.

Setup guide

Set up Code Climate 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 Code Climate 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="Code Climate_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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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="Code Climate_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Code Climate 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 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 AutoGen

Install autogen-ext[mcp] and use mcp_server_tools with your server URL. Pass the resulting tool list directly to your AssistantAgent constructor.

Yes, you can share the tools list across several agents. The security agent can check list_snapshot_code_issues while the manager agent tracks overall grades using the MCP client.

Authentication is managed by Vinkius. Your agents make requests using a single endpoint token, removing the need to pass raw credentials to individual agents.

This integration supports both stdio and Streamable HTTP transports. You configure the connection details inside the server parameters when initializing your client.

All MCP API requests run inside isolated, zero-trust V8 sandboxes. Your snapshot quality details and code issues are processed entirely in-memory and discarded immediately after the tool execution ends.

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