py-spy MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@py-spy MCP ServerGenerate a flamegraph for the Python process running my Flask app"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
py-spy MCP Server
A Model Context Protocol (MCP) server that exposes Python performance testing tools powered by py-spy.
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Profile Python in context. Sample live processes, generate flamegraphs, dump stacks, and compare runs â all through MCP.
Features
Profile by PID or command â sample a running Python process or launch a new one directly.
record_profileâ generate profiles in multiple formats:speedscope(interactive JSON)flamegraph(self-contained SVG)raw(stack-count text)chrometrace(Chrome DevTools timeline JSON)
dump_stacksâ capture the current Python call stacks of a process as JSON or human-readable text.list_python_processesâ list running Python processes on the machine to pick a target.analyze_profileâ parse an existing profile and return the hottest frames.compare_profilesâ compare two speedscope profiles and show percentage changes.top_profileâ run a shortpy-spy topsession and return a summary.On Windows,
py-spy topcannot be captured through a pipe, so this tool falls back to a short raw recording and returns the hottest frames.
Low-overhead sampling â powered by py-spy; reads process memory without modifying or running inside the target process.
Cross-platform â works on Linux, macOS, and Windows (subject to OS permissions).
Local-source friendly â during development the server automatically prefers a
py-spybinary built from the sibling Rust source (src/pyspy/).Optional native/C extension profiling â enable
--nativewhere the platform supports it.GIL and idle filtering â focus on active threads or GIL-holding threads.
Related MCP server: debugpy-mcp
Installation (from PyPI)
Using pip:
pip install pyspy-mcpUsing uv:
uv pip install pyspy-mcp
# or install as a global tool
uv tool install pyspy-mcpThis 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-mcpThe 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 -vThe 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-spyPublishing 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
ptracepermissions (sudoorcap_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.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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