What runtime does Pytest Mcp Server require?
Node.js 18.19.0 or higher and npm or yarn.
@tosin2013
Basic information
A Model Context Protocol (MCP) server for debugging pytest failures using systematic debugging principles.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"pytest-mcp-server": {
"command": "pytest-mcp-server",
"args": [
"start"
],
"env": {
"DATA_DIR": "./pytest-data"
}
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Pytest Mcp Server is an MCP server for debugging pytest failures using systematic debugging principles. It provides tools to register, analyze, and resolve test failures, and is production‑ready for use with MCP clients.
Install globally via npm install -g pytest-mcp-server. Add to an MCP client (e.g., Claude Desktop) with command pytest-mcp-server start or run as HTTP server using pytest-mcp-server start-http. Data directory is configurable via the DATA_DIR environment variable (default ./data).
Node.js 18.19.0 or higher and npm or yarn.
Data is stored in JSON files (`failures.json` and `debug_sessions.json`) in the `DATA_DIR` directory (default `./data`).
Yes, it is fully functional and has been tested with MCP Inspector and real MCP clients. All 8 tools work correctly.
mcp-framework 0.2.13 returns validation errors with `"type": "error"` instead of the MCP‑compliant `"type": "text"`. This only affects the MCP Testing Framework – real usage is unaffected.
Add a JSON entry to your Claude Desktop MCP configuration with command `pytest-mcp-server` and arguments `["start"]`. You can set `DATA_DIR` in the environment variables.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,

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