Skim MCP server

skim

Token-efficient skim-then-expand I/O for agentic models (Claude Code / desktop Claude).

Independent community project — not affiliated with, endorsed by, or sponsored by Anthropic.

No telemetry; runs entirely on your machine. See Trademarks, privacy & license.

Instead of reading a whole large file into context, the model calls skimopen(path) and gets a compact skeleton — structure, signatures, and (for logs/data) preserved critical values like ids, numbers, dates, and error codes — plus anchor ids. It reads the skeleton cheaply, then calls skimexpand(handle, anchors=[...]) to pull only the exact spans it needs, verbatim and lossless.

Compression is lazy, not lossy: nothing is paraphrased or destroyed, only deferred. Expansion is always one call away — which is what makes it safe for a closed model that can't ingest latent vectors.

What it does that other tools don't

The mainstream tools are lossy in context — repo-maps and --compress drop function bodies; summarizers and compression models paraphrase. The closest neighbors either cover code only, or show the model a transformed view and keep originals in a side cache. skim's line is stricter: whatever lands in context is verbatim source, and everything not shown is one anchored expand away — an agent can edit code from what it read without re-reading. That holds everywhere:

are promoted into the skeleton, never silently dropped) and dedup of repeated blocks.

• Files — Python (ast) + ~17 languages (tree-sitter); bodies folded, one expand away.
• Whole repos — skim_repo builds a ranked, token-budgeted map; expand exact code from any file.
• Command output — skim_run compresses verbose test / build / log output, fully recoverable.
• Data & logs — a generic path with a retention guarantee (ids, numbers, error codes, negations

See DESIGN.md for the architecture and verified prior-art positioning.

Falsifiable, not claimed

A reduction percentage is marketing until you can check it. skim ships the checker:

uv run skim-verify path/to/your/gnarliest_file.py     # any file at all; exit code tells CI

Five invariants, verified on your files, locally: every non-blank line recoverable, expands byte-exact, anchors in-bounds, reconstruction equal to the decoded file, deterministic output. The test suite enforces the same contract with Hypothesis fuzzing on every path; a reproducible FAIL on any readable file is a bug — please report it. Summarize-first tools cannot ship this command, because for them the equivalent check fails by design.

The cost-vs-correctness question has its own open yardstick — eval/ACCURACY.md prices every eval question under a full read vs skim (including the rows where skim loses), and any other context tool can be scored under the same protocol.

Built to be audited

Shortened. The full README is on GitHub.