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How to integrate Codacy MCP with Autogen

Connect Autogen to Codacy MCP. List all projects in your codacy account, show details for your active codacy organizations, and more using natural language, with authentication handled for you.

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Codacy is an automated code review platform that monitors code quality and technical debt. It helps teams enforce coding standards and ship healthier code.

18 Tools

Introduction

This guide walks you through connecting Codacy to AutoGen using the Composio tool router. By the end, you'll have a working Codacy agent that can list analyzed repositories, browse analysis tools and code patterns, check repository language settings, and list your organizations through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a Codacy account through Composio's Codacy MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Codacy with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIPydantic AI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Codacy
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Codacy tools
  • Run a live chat loop where you ask the agent to perform Codacy operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the Codacy MCP server, and what's possible with it?

The Codacy MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Codacy account. It provides structured and secure access to your code quality dashboard, so your agent can perform actions like listing projects, managing API tokens, checking organization repositories, and retrieving user account details on your behalf.

  • Automated project listing and discovery: Instantly fetch a comprehensive list of all projects accessible to your Codacy account for quick overview and navigation.
  • Organization and repository management: Ask your agent to enumerate all organizations you belong to and drill into the repositories associated with each, helping you keep track of where your code lives.
  • API token lifecycle management: Effortlessly create or delete API tokens as needed, making it easy to manage secure integrations and access controls without leaving your flow.
  • User account insights and verification: Retrieve account details to confirm authentication, audit user info, or set up new integrations with confidence.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step08 STEPS
1

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Codacy account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Codacy via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Codacy connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

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

load_dotenv()

async def main():
    # Initialize Composio and create a Codacy session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["codacy"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Codacy tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Codacy assistant agent with MCP tools
    agent = AssistantAgent(
        name="codacy_assistant",
        description="An AI assistant that helps with Codacy operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Codacy tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Codacy related question or task to the agent.\n")

# Conversation loop
while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    print("\nAgent is thinking...\n")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Codacy tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Codacy and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

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

load_dotenv()

async def main():
    # Initialize Composio and create a Codacy session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["codacy"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Codacy assistant agent with MCP tools
        agent = AssistantAgent(
            name="codacy_assistant",
            description="An AI assistant that helps with Codacy operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Codacy related question or task to the agent.\n")

        # Conversation loop
        while True:
            user_input = input("You: ").strip()

            if user_input.lower() in ['exit', 'quit', 'bye']:
                print("\nGoodbye!")
                break

            if not user_input:
                continue

            print("\nAgent is thinking...\n")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You now have an Autogen assistant wired into Codacy through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Codacy, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

Every Codacy action and event your agent gets out of the box.

Create API Token

Creates a new account API token for the authenticated user.

Delete API Token

Tool to delete a specific API token from the authenticated user's account.

Get Account Details

Tool to retrieve details of the authenticated user's account.

Get Configuration Status

Tool to retrieve the current configuration status of the Codacy system.

Get Health

Tool to check the health status of the Codacy API.

Get Organizations Repositories Settings Languages

Tool to get the list of all languages with their extensions and enabled status for a repository.

Get Tool Pattern

Tool to retrieve the definition of a specific pattern for a given tool.

Get User Organizations

Retrieves all organizations the authenticated user belongs to for a specific Git provider.

Get Version

Tool to retrieve the version of the Codacy installation.

List Analysis Organizations Repositories

List repositories with analysis information for a specified organization, optionally filtering by name.

List Duplication Tools

Tool to retrieve the list of duplication detection tools available in Codacy.

List Languages and Tools

Tool to retrieve the list of languages supported by available tools.

List Login Integrations

Tool to list configured login providers on Codacy's platform.

List Metrics Tools

Tool to retrieve the list of metrics tools available in Codacy.

List Projects

List projects accessible to the authenticated user, with organization and name filters and page parameters.

List Provider Integrations

Tool to list provider integrations existing on Codacy's platform.

List Tools

Tool to retrieve the list of analysis tools available in Codacy.

List Tools Patterns

Tool to retrieve the list of patterns for a specific tool.

FRAMEWORKS

How to build Codacy MCP Agent with another framework

Claude Code logo

Claude Code

Use Codacy MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Codacy MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Codacy MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Codacy MCP with Claude Agent SDK

Codex logo

Codex

Use Codacy MCP with Codex

OpenClaw logo

OpenClaw

Use Codacy MCP with OpenClaw

Hermes logo

Hermes

Use Codacy MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Codacy MCP with Atomic Agent

Google ADK logo

Google ADK

Use Codacy MCP with Google ADK

LangChain logo

LangChain

Use Codacy MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Codacy MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Codacy MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Codacy MCP with LlamaIndex

CrewAI logo

CrewAI

Use Codacy MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Codacy MCP with Pydantic AI

FAQ

Frequently asked questions

With a standalone Codacy MCP server, the agents and LLMs can only access a fixed set of Codacy tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Codacy and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. Autogen fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Codacy tools.

Yes, absolutely. You can configure which Codacy scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Codacy data and credentials are handled as safely as possible.

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