py-spy MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| record_profileA | Record a sampling profile of a Python process or command. |
| dump_stacksA | Dump the current Python call stacks of a process. |
| list_python_processesA | List running Python processes on this machine. Returns: A table of PID, memory usage, and command line. |
| analyze_profileA | Analyze an existing py-spy profile and return the hottest frames. |
| compare_profilesA | Compare two speedscope profiles and show percentage changes. |
| top_profileA | Run a live On Windows, |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| python_processes_resource | Return a JSON list of currently running Python processes. |
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose: listing processes, recording, analyzing, comparing, dumping stacks, and live top view. No two tools overlap, making selection unambiguous for an agent.
Most tools follow a verb_noun pattern (e.g., list_python_processes, record_profile). The tool 'top_profile' deviates slightly by using 'top' as a verb, but it is still interpretable. Overall consistent.
With 6 tools, the set covers all essential py-spy operations without being excessive. Each tool earns its place for a focused profiling server.
The tools cover the full lifecycle of profiling: process discovery, recording, analysis, comparison, stack inspection, and live monitoring. No major gaps are apparent for the intended use case.