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firelock-ai/kin

firelock-ai/kin

Graph-native code repository that shows what a
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collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
Third-party quality signals

A new foundation for code.

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**Kin is a graph-native code repository for AI agents and the people who build with them.** It stores source, recorded code relationships, and versioned history as repository state. The graph is the repository model, not a search index maintained beside another repository.
Functions, types, and the relationships between them are data you commit, branch, and merge. Exact source is preserved byte for byte, and filesystem projections let supported tools keep working with ordinary files.
**Public beta.** Try Kin on a real project you know well. Expect rough edges.
Quickstart · Documentation · Browser demo
A star helps other people find Kin, and Discussions is where to bring a question about it.
See what connects
Before changing a shared function, what else should you inspect? Kin lets you look up its recorded callers and explore related code. The CLI and MCP server query the same graph, so you and your agent can work from the same record.
*Recorded on a prepared ripgrep graph at e89fff89ac9af12e8d4ce9d5fd07beb408ca730f. Raw run artifacts are not public. This illustrates a workflow, not a performance benchmark.*
Use it from Claude Code, Codex or Cursor
For Claude Code:
For Codex, add the marketplace and install the plugin, or let kin setup --intent agent write the MCP server into ~/.codex/config.toml for you.
For Cursor, add the MCP server by hand; see plugins/kin-cursor for the exact snippet.
After installing, run kin init . in a fresh clone of a project you know well; the kin-setup skill walks you through the rest.
Kin is not published on crates.io. The kin crate there is an unrelated project.
Quickstart
Start in a fresh, full clone of a project you know well. kin init reads your Git history without changing it or your tracked files. It keeps its store outside your checkout, in ~/.kin/stores, and writes nothing into the repository; kin store path prints where a checkout's store is. By default it admits the checked-out commit first, so questions answer as soon as that tree is read, and then imports every commit your branches and tags reach in the background, at low priority; kin init --history full imports the whole history up front, and --history none never imports it. Importing history takes time, memory and disk that grow with history rather than with the size of the checkout. Before it starts, kin init checks memory and free disk and stops with the numbers when it can already tell the machine is short. **A shallow clone admits only its checked-out commit, and submodules and Git LFS are not supported**, and Git hooks, a sparse checkout or an unfinished merge or rebase also stop the import. kin init names the fix for each, and a fresh clone avoids most of them.
1. Install
On macOS, Linux and WSL2, one command installs Kin and connects the AI coding tools it
finds. It needs Node.js 20 or newer:
On a machine without Node, run the installer instead. get.kinlab.ai and get.kinlab.dev
serve the same script:
Either way, reload your shell as a separate command, because the install puts kin in
~/.kin/bin and adds that directory to your shell profile for new sessions:
On native Windows x64, install from PowerShell with irm https://get.kinlab.dev/install.ps1 | iex.
It installs the kin CLI and does not connect AI coding tools, because WSL2 remains the
recommended path on Windows. The Windows entry under Beta limits
says what works there. No native Windows ARM64 build is published. On an ARM64 machine, run
that line from x64 PowerShell to install the x86_64 build under emulation, or use WSL2.
The installer adds kin to your user PATH, so open a new PowerShell window in place of
exec "$SHELL" -l before the next step.
Source
awesome · https://github.com/firelock-ai/kin
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