codemunch

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The problem

When Claude Code explores a codebase, the naive approach is to read whole files. An 800-line file costs ~8,000 tokens. Read ten files to find one function and you've burned 80,000 tokens before writing a single line of code.

Other solutions add an MCP server, a Python runtime, or a database — all of which consume their own resources and add complexity. codemunch takes a different approach: a pure Claude Code plugin that runs with zero infrastructure overhead.

codemunch fixes this. It auto-indexes your codebase into a flat JSON file and lets Claude fetch the exact 20 lines it needs instead of the 800-line file. No server process, no database daemon, no Python dependency — just install and start using it.

Without codemunch:  read auth.ts (800 lines) → ~8,000 tokens
With codemunch:     fetch validateToken()     →    ~35 tokens

Savings: 99.6%

Why use codemunch?

Claude Code bills by token. Every file read costs tokens — and most of those tokens are wasted on code you didn't need to see.

Benchmarked context savings

We benchmarked codemunch against three real open-source repos — running 5 typical exploration tasks on each and measuring token consumption with vs without codemunch:

Best case: 99.0% savings (finding all references to .send() across 139 test files — refs instead of grep + reading files). Worst case: 69.8% savings (multi-fetch of related functions — still cheaper than reading one full file).

Full benchmark methodology and per-task breakdown: docs/benchmark-results.md

That's ~22x less context usage on average, which means:

• Longer conversations — you stay well within Claude's context window instead of hitting limits mid-task
• Lower costs — fewer tokens consumed per task directly reduces your API bill
• Faster responses — less input for Claude to process means quicker replies
• Better results — Claude sees only the relevant code, not thousands of lines of noise, leading to more focused and accurate responses

How it works

codemunch uses a three-tier engine — it picks the best available tool per language and falls back automatically. No configuration required.

Tier 1 — LSP (Language Server)
  Byte-exact symbol boundaries, type signatures, cross-file references.
  Same engine powering "Go to Definition" in VS Code.
         ↓ not available?
Tier 2 — Universal ctags
  40+ languages. Near-exact boundaries. Ships with most Unix systems.
         ↓ not available?
Tier 3 — ripgrep
  Works on literally any language via regex patterns.
  If rg is installed, codemunch works.

Auto-indexing

You never need to manually index. codemunch automatically: