What are the runtime requirements?

The server requires Python and the tools (pylint, pytest, mypy) to be installed in a virtual environment. The `--python-executable` or `--venv-path` must point to that environment, not the project’s runtime venv. Installation is done via `pip install git+https://github.com/MarcusJellinghaus/mcp-tools-py.git`.

Where does the data live?

All operations are performed on the local file system within the specified `--project-dir`. No data is sent externally. Temporary files are created during test execution and cleaned up unless `--keep-temp-files` is used.

What credentials does it need?

It reads `PYTHONPATH` from the environment. Store these in your client's env block or a secrets manager — never commit them to a repository — and grant the narrowest scope that still covers your use case.

MCP Code Checker MCP Server — Install Guide & Tools

Name: MCP Code Checker MCP Server
Author: MarcusJellinghaus

What is the MCP Code Checker MCP server?

MCP server providing code quality checks (pylint and pytest) with smart LLM-friendly prompts for analysis and fixes. Enables Claude and other AI assistants to analyze your code and suggest improvements. Exposed over MCP by the mcp code checker mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.

What it actually does

A Model Context Protocol (MCP) server providing code quality checking operations with easy client configuration. This server offers an API for performing code quality checks within a specified project directory, following the MCP protocol design.

This MCP server enables AI assistants like Claude (via Claude Desktop), VSCode with GitHub Copilot, or other MCP-compatible clients to run code quality checks on Python projects. The tools provided are:

run_pylint_check: Run pylint on the project code and generate smart prompts for LLMs
run_pytest_check: Run pytest on the project code and generate smart prompts for LLMs
run_mypy_check: Run mypy type checking on the project code

Its toolset

Everything the assistant can do here goes through one of these:

Notes — The Notes tool exposed by this server
Troubleshooting — The Troubleshooting tool exposed by this server

Adding it to your client

Installation goes through your MCP client rather than a global install: point it at @modelcontextprotocol/inspector on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.

Configuration

You will need one environment variable: PYTHONPATH. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

When to reach for it

Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. MCP Code Checker's toolset — Notes, Troubleshooting — is a fair guide to whether it matches your workflow. It is maintained by MarcusJellinghaus; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against MCP Code Checker's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Caveats

It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
MCP clients confirm each tool call by default. Leave that on until you have watched what the mcp code checker mcp server does with a few real requests.

Tool	What it does
Notes	The Notes tool exposed by this server.
Troubleshooting	The Troubleshooting tool exposed by this server.

Tool

What it does

Notes

The Notes tool exposed by this server.

Troubleshooting

The Troubleshooting tool exposed by this server.

How to install the MCP Code Checker MCP server

{
    "mcpServers": {
        "mcp-tools-py": {
            "command": "mcp-tools-py",
            "args": [
                "--project-dir", "/path/to/your/project",
                "--venv-path", "${VIRTUAL_ENV}"
            ]
        }
    }
}

Configuration as documented by the project. Restart the client after saving.

Variable	Description	Required
PYTHONPATH	Filesystem location the server is allowed to use.	Optional

Variable

Description

Required

PYTHONPATH

Filesystem location the server is allowed to use.

Optional

Frequently asked questions

The server provides a more controlled environment: only pylint, pytest, and mypy can be run, all operations are confined to the specified project directory, and output is limited and formatted to reduce context consumption. This enhances security and transparency compared to a general-purpose bash MCP tool.

MCP Code Checker MCP Server

What is the MCP Code Checker MCP server?

What it actually does

Its toolset

Adding it to your client

Configuration

When to reach for it

Caveats

Available tools

How to install the MCP Code Checker MCP server

Configuration

Example prompts to try

Frequently asked questions

Alternatives to the MCP Code Checker MCP server

Context7

Playwright

GitHub

Linear

Git

Time

MCP Code Checker MCP Server

What is the MCP Code Checker MCP server?

What it actually does

Its toolset

Adding it to your client

Configuration

When to reach for it

Caveats

Available tools

How to install the MCP Code Checker MCP server

Configuration

Example prompts to try

Frequently asked questions

How does this differ from giving an AI assistant bash access?

What are the runtime requirements?

Where does the data live?

What credentials does it need?

Alternatives to the MCP Code Checker MCP server

Context7

Playwright

GitHub

Linear

Git

Time