# How to integrate Codacy MCP with Pydantic AI

```json
{
  "title": "How to integrate Codacy MCP with Pydantic AI",
  "toolkit": "Codacy",
  "toolkit_slug": "codacy",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/codacy/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/codacy/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:06:58.410Z"
}
```

## Introduction

This guide walks you through connecting Codacy to Pydantic AI using the Composio tool router. By the end, you'll have a working Codacy agent that can list all projects in your codacy account, show details for your active codacy organizations, enumerate repositories for a specific organization through natural language commands.
This guide will help you understand how to give your Pydantic AI 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

- [OpenAI Agents SDK](https://composio.dev/toolkits/codacy/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/codacy/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/codacy/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/codacy/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/codacy/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/codacy/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/codacy/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/codacy/framework/cli)
- [Google ADK](https://composio.dev/toolkits/codacy/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/codacy/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/codacy/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/codacy/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/codacy/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/codacy/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- How to set up your Composio API key and User ID
- How to create a Composio Tool Router session for Codacy
- How to attach an MCP Server to a Pydantic AI agent
- How to stream responses and maintain chat history
- How to build a simple REPL-style chat interface to test your Codacy workflows

## What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.
Key features include:
- Type Safety: Built on Pydantic for automatic data validation
- MCP Support: Native support for Model Context Protocol servers
- Streaming: Built-in support for streaming responses
- Async First: Designed for async/await patterns

## 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.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CODACY_CREATE_API_TOKEN` | Create API Token | Creates a new account API token for the authenticated user. The token inherits all permissions from the account owner and provides access to the same organizations and repositories. Note: The token is created with default settings. To configure expiration dates or other settings, use the Codacy web interface. The newly created token can be used to authenticate API requests by including it in the 'api-token' header. |
| `CODACY_DELETE_API_TOKEN` | Delete API Token | Tool to delete a specific API token from the authenticated user's account. Use after confirming the token ID. |
| `CODACY_GET_ACCOUNT_DETAILS` | Get Account Details | Tool to retrieve details of the authenticated user's account. Use when confirming authentication before user-level operations. |
| `CODACY_GET_CONFIGURATION_STATUS` | Get Configuration Status | Tool to retrieve the current configuration status of the Codacy system. Use when checking system setup completion or first-time configuration status. |
| `CODACY_GET_HEALTH` | Get Health | Tool to check the health status of the Codacy API. Use when verifying API connectivity and service availability. |
| `CODACY_GET_ORGANIZATIONS_REPOSITORIES_SETTINGS_LANGUAGES` | Get Organizations Repositories Settings Languages | Tool to get the list of all languages with their extensions and enabled status for a repository. Use when you need to understand which programming languages are detected and enabled for analysis in a specific Codacy repository. |
| `CODACY_GET_TOOL_PATTERN` | Get Tool Pattern | Tool to retrieve the definition of a specific pattern for a given tool. Use when you need to get detailed information about a specific code pattern including its description, examples, parameters, and configuration. |
| `CODACY_GET_USER_ORGANIZATIONS` | Get User Organizations | Retrieves all organizations the authenticated user belongs to for a specific Git provider. Returns organization details including name, provider, avatar, access permissions (DAST, SCA), and join status. Use this to discover which organizations a user can access on Codacy for a given Git provider (GitHub, GitLab, or Bitbucket). Requires the user to have connected the specified provider to their Codacy account. |
| `CODACY_GET_VERSION` | Get Version | Tool to retrieve the version of the Codacy installation. Use when checking the Codacy API version for compatibility or debugging purposes. |
| `CODACY_LIST_ANALYSIS_ORGANIZATIONS_REPOSITORIES` | List Analysis Organizations Repositories | Tool to list organization repositories with analysis information for the authenticated user. Use when you need to retrieve repositories from a specific organization with their analysis status. For Bitbucket, ensure you URL encode the cursor before using it in subsequent API calls. |
| `CODACY_LIST_DUPLICATION_TOOLS` | List Duplication Tools | Tool to retrieve the list of duplication detection tools available in Codacy. Use when you need to identify which tools can analyze code duplication for different programming languages. |
| `CODACY_LIST_LANGUAGES_TOOLS` | List Languages and Tools | Tool to retrieve the list of languages supported by available tools. Use when you need to determine which programming languages are supported by Codacy's analysis tools. |
| `CODACY_LIST_LOGIN_INTEGRATIONS` | List Login Integrations | Tool to list configured login providers on Codacy's platform. Use when you need to discover available authentication methods for Codacy login. |
| `CODACY_LIST_METRICS_TOOLS` | List Metrics Tools | Tool to retrieve the list of metrics tools available in Codacy. Use when you need to discover which tools calculate metrics on projects and which languages they support. |
| `CODACY_LIST_PROJECTS` | List Projects | Tool to list all projects accessible to the authenticated user. Use when you need a list of repositories after confirming API token validity. |
| `CODACY_LIST_PROVIDER_INTEGRATIONS` | List Provider Integrations | Tool to list provider integrations existing on Codacy's platform. Use when you need to discover available Git providers that can be integrated with Codacy for authentication and repository management. |
| `CODACY_LIST_TOOLS` | List Tools | Tool to retrieve the list of analysis tools available in Codacy. Use when you need to identify which code analysis tools are available and which programming languages they support. |
| `CODACY_LIST_TOOLS_PATTERNS` | List Tools Patterns | Tool to retrieve the list of patterns for a specific tool. Returns code patterns that the tool can use to find issues, with pagination support. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Codacy MCP server is an implementation of the Model Context Protocol that connects your AI agent to Codacy. It provides structured and secure access so your agent can perform Codacy operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before starting, make sure you have:
- Python 3.9 or higher
- A Composio account with an active API key
- Basic familiarity with Python and async programming

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install the required libraries.
What's happening:
- composio connects your agent to external SaaS tools like Codacy
- pydantic-ai lets you create structured AI agents with tool support
- python-dotenv loads your environment variables securely from a .env file
```bash
pip install composio pydantic-ai python-dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your agent to Composio's API
- USER_ID associates your session with your account for secure tool access
- OPENAI_API_KEY to access OpenAI LLMs
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key
```

### 4. Import dependencies

What's happening:
- We load environment variables and import required modules
- Composio manages connections to Codacy
- MCPServerStreamableHTTP connects to the Codacy MCP server endpoint
- Agent from Pydantic AI lets you define and run the AI assistant
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
```

### 5. Create a Tool Router Session

What's happening:
- We're creating a Tool Router session that gives your agent access to Codacy tools
- The create method takes the user ID and specifies which toolkits should be available
- The returned session.mcp.url is the MCP server URL that your agent will use
```python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Codacy
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["codacy"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
```

### 6. Initialize the Pydantic AI Agent

What's happening:
- The MCP client connects to the Codacy endpoint
- The agent uses GPT-5 to interpret user commands and perform Codacy operations
- The instructions field defines the agent's role and behavior
```python
# Attach the MCP server to a Pydantic AI Agent
codacy_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[codacy_mcp],
    instructions=(
        "You are a Codacy assistant. Use Codacy tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
```

### 7. Build the chat interface

What's happening:
- The agent reads input from the terminal and streams its response
- Codacy API calls happen automatically under the hood
- The model keeps conversation history to maintain context across turns
```python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Codacy.\n")

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", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
```

### 8. Run the application

What's happening:
- The asyncio loop launches the agent and keeps it running until you exit
```python
if __name__ == "__main__":
    asyncio.run(main())
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Codacy
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["codacy"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    codacy_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[codacy_mcp],
        instructions=(
            "You are a Codacy assistant. Use Codacy tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Codacy.\n")

    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", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

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

## Conclusion

You've built a Pydantic AI agent that can interact with Codacy through Composio's Tool Router. With this setup, your agent can perform real Codacy actions through natural language.
You can extend this further by:
- Adding other toolkits like Gmail, HubSpot, or Salesforce
- Building a web-based chat interface around this agent
- Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Codacy for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

## How to build Codacy MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/codacy/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/codacy/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/codacy/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/codacy/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/codacy/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/codacy/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/codacy/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/codacy/framework/cli)
- [Google ADK](https://composio.dev/toolkits/codacy/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/codacy/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/codacy/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/codacy/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/codacy/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/codacy/framework/crew-ai)

## Related Toolkits

- [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure.
- [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms.
- [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place.
- [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences.
- [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses.
- [Alchemy](https://composio.dev/toolkits/alchemy) - Alchemy is a blockchain development platform offering APIs and tools for Ethereum apps. It simplifies building and scaling Web3 projects with robust infrastructure.
- [Algolia](https://composio.dev/toolkits/algolia) - Algolia is a hosted search API that powers lightning-fast, relevant search experiences for web and mobile apps. It helps developers deliver instant, typo-tolerant, and scalable search without complex infrastructure.
- [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction.
- [Apiflash](https://composio.dev/toolkits/apiflash) - Apiflash is a website screenshot API for programmatically capturing web pages. It delivers high-quality screenshots on demand for automation, monitoring, or reporting.
- [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache.
- [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence.
- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Codacy MCP?

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.

### Can I use Tool Router MCP with Pydantic AI?

Yes, you can. Pydantic AI 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.

### Can I manage the permissions and scopes for Codacy while using Tool Router?

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.

### How safe is my data with Composio Tool Router?

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.

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
