# py-spy MCP Server

> py-spy MCP Server — lburny-pyspy-mcp. Use this tool when you need to profile and optimize Python processes, as it provides detailed insights through flamegraphs, stack dumps, and performance comparisons. The py-spy MCP Server takes Python process IDs or names as input and outputs visualizable data for performance analysis. It is ideal for identifying performance bottlenecks and debugging issues in Python applications.

Canonical page: https://skillsregistry.net/skills/lburny-pyspy-mcp  
JSON: https://api.skillsregistry.net/v1/skills/lburny-pyspy-mcp

## Description

MCP server for profiling Python processes using py-spy, supporting flamegraphs, stack dumps, and performance comparisons.

## Trust

- **Trust score (0–1):** 0.55
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/fn3gaxvyi9)
- **Repository:** <https://github.com/LBurny/pyspy-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "lburny-pyspy-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/lburny-pyspy-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/lburny-pyspy-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt