Scout APM
Scout Monitoring MCP provides AI assistants with direct access to Scout APM performance monitoring data through a comprehensive set of tools for querying application metrics, traces, errors, and performance insights. Built by Scout Monitoring using Python and FastMCP, it integrates with Scout's API to surface N+1 queries, memory bloat, slow queries, endpoint performance data, and detailed execution traces with line-of-code information that AI can use to target fixes directly in code editors. The server includes 8 specialized tools covering application listing, metric retrieval, endpoint analysis, trace inspection, and error group management, with built-in validation for time ranges and metric types, making it valuable for AI-assisted performance debugging, automated issue detection, and generating targeted pull requests that fix specific performance problems in Rails, Django, FastAPI, Laravel and other monitored applications.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- version-control
- Source
- PulseMCP
- Repository
- github.com/scoutapp/scout-mcp-local
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve Scout APM from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.