trace-mcp
Reduces code exploration time from ~42 minutes to a single tool call, cutting agent iteration overhead and inference cost when debugging or understanding unf…
An MCP server that builds a framework-aware graph of your codebase once, then serves it to AI agents so they reason from a precomputed structure instead of re-reading files every turn. Tools like `get_change_impact` return the blast radius of a change across languages and frameworks in a single call. Supports 80+ languages and also indexes markdown knowledge vaults such as Obsidian and Logseq. For teams using Claude Code or Codex on large or unfamiliar codebases.
- Trace execution path through unfamiliar codebase in seconds
- Identify root cause of bug across multiple files automatically
- Generate accurate dependency maps for legacy code modules
Reduces code exploration time from ~42 minutes to a single tool call, cutting agent iteration overhead and inference cost when debugging or understanding unfamiliar codebases.
Teams using Claude for code analysis, debugging, or refactoring who need fast codebase introspection without manual file navigation.
https://github.com/nikolai-vysotskyi/trace-mcp
By nikolai-vysotskyi
How to Get It
npm install -g trace-mcp && trace-mcp init && trace-mcp add
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Once it’s connected, paste this into Claude:
Help me trace execution path through unfamiliar codebase in seconds
Trust Signals Auto-scanned
Data & Access
Community Pulse Active
Discussed on Hacker News, Reddit
- Xcode Trace Analyzer MCP — Reddit · 15 pts
- Trace your LLM API and MCP calls with zero code changes (eBPF, Linux) — Reddit · 13 pts
- Get an MCP server trace in 30 seconds — Reddit · 10 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 84 GitHub stars; contributors unknown; last commit 1d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 84 GitHub stars; contributors unknown; last commit 1d ago; license MIT.