Can I see the quality grade for a specific repository?

Yes! Use the `get_repository_quality_analysis` tool. Provide the provider (e.g., `gh`), organization, and repository name. The agent will return the current letter grade (A-F) and core quality metrics.

How do I search for security-related issues in my code?

Use the `search_repository_issues` tool. You can filter the payload to include `categories: ['Security']`. Your agent will fetch all security vulnerabilities identified by Codacy in that repository.

Where do I find my Codacy API Token?

Log in to Codacy, click on your avatar in the top right, go to **User Settings**, and select the **API** tab. You can generate and copy your account token from there.

Codacy MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: Codacy
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Codacy through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Codacy "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Codacy?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Codacy MCP Server

Connect your Codacy account to any AI agent and take full control of your automated code reviews and quality metrics through natural conversation. Streamline how you monitor security and maintainability across your repositories natively.

Pydantic AI validates every Codacy tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Organization Oversight — List and retrieve details for all organizations associated with your Codacy account natively
Repository Intelligence — Access current quality grades, complex files, and overall metrics for any analyzed repository flawlessly
Issue Management — Search for specific code quality issues using advanced filters like level, category, and language securely
Language Logistics — List all programming languages supported by the Codacy analysis engine flawlessly
Member Management — Access organization member rosters and user profile information securely
Webhook Visibility — Monitor configured webhooks for real-time quality and analysis notifications directly within your workspace

The Codacy MCP Server exposes 8 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Codacy to Pydantic AI via MCP

Follow these steps to integrate the Codacy MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from Codacy with type-safe schemas

Why Use Pydantic AI with the Codacy MCP Server

Pydantic AI provides unique advantages when paired with Codacy through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Codacy integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Codacy connection logic from agent behavior for testable, maintainable code

Codacy + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Codacy MCP Server delivers measurable value.

Type-safe data pipelines: query Codacy with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Codacy tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Codacy and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Codacy responses and write comprehensive agent tests

Codacy MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect Codacy to Pydantic AI via MCP:

get_my_codacy_profile

Retrieve information about the authenticated Codacy user

get_repository_quality_analysis

Get the current quality grade and metrics for a specific repository

list_codacy_organizations

List all organizations associated with the account

list_organization_members

List people and users belonging to an organization

list_organization_repositories

List all repositories analyzed within an organization

list_repository_webhooks

List configured webhooks for quality notifications

list_supported_languages

List programming languages supported by the Codacy analysis engine

search_repository_issues

Search for specific code quality issues in a repository

Example Prompts for Codacy in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Codacy immediately.

"List all repositories in the 'vinkius' organization on GitHub."

"Show me the security issues for the 'core-api' repository."

"What languages does Codacy support?"

Troubleshooting Codacy MCP Server with Pydantic AI

Common issues when connecting Codacy to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Codacy + Pydantic AI FAQ

Common questions about integrating Codacy MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Codacy MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.