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MCP file tools silently eat your context window.I built one that doesnt

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Hi, I am Anthony.Every token your filesystem tools consume is context the model cannot use for reasoning. Most MCP file servers are O(file size) on every operation: reads return the whole file, edits rewrite the whole file. The context window fills up before the agent gets anything meaningful done, and the problem compounds silently as your files grow.Chisel makes edits O(diff) and reads O(match). The agent sends a unified diff instead of a full rewrite, and queries with grep or sed instead of reading entire files. On a 500-line file this is nearly two orders of magnitude less context per operation. The savings scale linearly with file size, so the larger your codebase, the more it matters.The other thing I cared about was security. Path confinement is enforced at the kernel level via cap-std and openat with O_NOFOLLOW, not a userspace prefix check. Shell commands run via direct execve against a fixed compile-time whitelist — no sh -c wrapper, no arbitrary execution. Atomic writes use a tmp-and-rename so a failed patch never corrupts the target file.It ships as a standalone MCP server, as chisel-core, a plain sync Rust library you can embed in your own MCP server, and as a WASM build for Node.js and Python runtimes, you can bring your own MCP and build on top of it.Would love feedback, especially from anyone building agents that do heavy file manipulation.GitHub: https://github.com/ckanthony/Chisel

HN · launched Mar 1, 2026 · 6 upvotes (top 71%) · 0 views

Niche: model context protocol tools · 465 launches, 13 in the last 7 days ▼ -24% · Explore this niche →

Category and tags

  • Horizontal
  • Agent / copilot
  • Developer
  • AI-native
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

Yes This is a Model Context Protocol (MCP) server that provides efficient file manipulation tools (like diffs, pagination, or targeted line reads) using standard Node.js or Python file I/O libraries.

Discussion

9 comments analyzed.

Competitors mentioned: GitHub Copilot Chat, Roocode

Concerns raised: Token cost savings not quantified, Integration with GitHub Copilot Chat unclear

Feature requests: Token savings comparison vs vanilla approach, Context cost metrics and benchmarks

Competitors

Other products that read as similar to this one : 387 launches clear the similarity bar, closest 8 shown.

Attention rank: #323 of 388 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 115 days after the earliest competitor.

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