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LBurny

py-spy MCP Server

by LBurny

py-spy MCP Server

A Model Context Protocol (MCP) server that exposes Python performance testing tools powered by py-spy.

License: MIT Python 3.10+ MCP Compatible tests passing

๐ŸŒ English | ็ฎ€ไฝ“ไธญๆ–‡

Profile Python in context. Sample live processes, generate flamegraphs, dump stacks, and compare runs โ€” all through MCP.

Features

  • Profile by PID or command โ€” sample a running Python process or launch a new one directly.

  • record_profile โ€” generate profiles in multiple formats:

    • speedscope (interactive JSON)

    • flamegraph (self-contained SVG)

    • raw (stack-count text)

    • chrometrace (Chrome DevTools timeline JSON)

  • dump_stacks โ€” capture the current Python call stacks of a process as JSON or human-readable text.

  • list_python_processes โ€” list running Python processes on the machine to pick a target.

  • analyze_profile โ€” parse an existing profile and return the hottest frames.

  • compare_profiles โ€” compare two speedscope profiles and show percentage changes.

  • top_profile โ€” run a short py-spy top session and return a summary.

    • On Windows, py-spy top cannot be captured through a pipe, so this tool falls back to a short raw recording and returns the hottest frames.

  • Low-overhead sampling โ€” powered by py-spy; reads process memory without modifying or running inside the target process.

  • Cross-platform โ€” works on Linux, macOS, and Windows (subject to OS permissions).

  • Local-source friendly โ€” during development the server automatically prefers a py-spy binary built from the sibling Rust source (src/pyspy/).

  • Optional native/C extension profiling โ€” enable --native where the platform supports it.

  • GIL and idle filtering โ€” focus on active threads or GIL-holding threads.

Related MCP server: javaperf

Installation (from PyPI)

Using pip:

pip install pyspy-mcp

Using uv:

uv pip install pyspy-mcp
# or install as a global tool
uv tool install pyspy-mcp

This will automatically install the compatible py-spy binary wheel for your platform.

Running with Claude Desktop / Claude Code

Add the server as a Local command connector:

{
  "mcpServers": {
    "pyspy": {
      "command": "pyspy-mcp"
    }
  }
}

Or run directly:

pyspy-mcp

The server speaks MCP over stdio.

Development (from source)

If you want to use the local py-spy Rust source instead of the PyPI package:

# Build py-spy from the local Rust source
cargo build --release

# The binary will be at:
#   target/release/py-spy        (Linux / macOS)
#   target/release/py-spy.exe    (Windows)

# Install the Python MCP package in editable mode
pip install -e ".[dev]"

# Or using uv
uv pip install -e ".[dev]"

# Run tests
python -m pytest tests/pyspy_mcp -v

The server will automatically prefer a locally built binary at target/release/py-spy[.exe] over the py-spy installed from PyPI. You can also force a specific binary by setting the environment variable:

export PYSPY_MCP_BINARY=/path/to/py-spy

Publishing to PyPI

python -m build
python -m twine upload dist/*

The published wheel is a pure-Python py3-none-any package and depends on the upstream py-spy PyPI package. If you modify the Rust source and want to ship those changes, you will need to build platform-specific wheels (or bundle the rebuilt py-spy binary as package data).

Permissions

  • On Linux, profiling an existing PID usually requires ptrace permissions (sudo or cap_sys_ptrace).

  • On macOS, profiling often requires root due to System Integrity Protection (SIP).

  • On Windows, running as Administrator may be needed for some processes.

Configuration

Set PYSPY_MCP_BINARY to override the bundled/development py-spy binary location.

Install Server
A
license - permissive license
A
quality
A
maintenance

Maintenance

โ€“Maintainers
โ€“Response time
0dRelease cycle
3Releases (12mo)
Commit activity

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