repofit

io.github.pth2002由 GitHub 帳號 pth2002 發布v0.1.1更新於 Nov 4, 2026

利用你的編碼代理已經瞭解到的關於你的資訊,找到適合你的 GitHub 專案。

AI 翻譯由 AI 模型根據下方的原文描述翻譯,可能有誤。

原文描述

Find GitHub projects that fit you, using what your coding agents already know about you.

已驗證STDIO僅桌面開發者工具

概覽

repofit 的本機 MCP 服務;無需登入;STDIO;10 個工具。

暫無 AI 概覽:以下資訊來自註冊中心條目和服務本身。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 repofit,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[repofit. Your agents already know you. Now they know what to install. A sketch: AGENTS.md, CLAUDE.md, Cursor rules and Gemini chats go into repofit, which reads them on your machine. Out come ntfy, SciencePlots and actionlint, each pointing back at the chat it came from.]

[Tests] [Python 3.11+] [No dependencies] [MCP server] [MIT]

Stop scrolling trending. Ask the agent that has watched you work.

Every week another wave of repositories hits ten thousand stars, and every "tools you should try" list is written for everyone at once. Meanwhile your coding agents have been taking notes on you for months: what you build, what keeps breaking, what you complained about at 2 a.m. repofit reads those notes on your own machine, from Claude Code, Codex, Cursor and a dozen more, and turns them into picks you have not heard of and will actually use. Every pick shows you the moment in your own history that earned it.

https://github.com/user-attachments/assets/c7ac0bcf-74ed-4a09-9295-b6d06e6d67c1

Install

bash
pipx install repofit

Then point the agents you use at repofit mcp. Most of them read the same MCP config:

json
{ "mcpServers": { "repofit": { "command": "repofit", "args": ["mcp"] } } }

That line goes in ~/.cursor/mcp.json for Cursor, ~/.gemini/settings.json for Gemini CLI, ~/.qwen/settings.json for Qwen Code, and the MCP settings of Cline, Windsurf or Claude Desktop. Codex reads TOML, and Claude Code adds servers from the command line:

toml
# ~/.codex/config.toml[mcp_servers.repofit]command = "repofit"args = ["mcp"]
bash
claude mcp add repofit -- repofit mcp

repofit runs inside your agent, so your agent's own model does the thinking: no API key, no account, nothing to host. To skip the install step, use uv and make the command uvx repofit mcp.

Just ask

Open a new session in any agent you connected and talk to it like a colleague who has read your history:

  • "Use repofit to recommend some GitHub projects for me."
  • "Does github.com/owner/name fit me?"
  • "Is there a good tool for turning PDFs into Markdown?"
  • "Which of my installed skills do I never use?"

The agent shows you the picks in the chat, and the same list stays one command away:

[Terminal output of repofit recommend --show. Three picks, each with the task it serves, why it fits and the session it was seen in: ntfy for training jobs on rented GPU servers, seen in a Claude Code session asking whether the run was done; SciencePlots for paper figures, seen in a Codex session about a chart layout; actionlint for GitHub Actions releases, seen in a Cursor session about a workflow typo. Below them: one skipped household name, installed skills and MCP servers no session ever called, and tools left out because they are already in use.]

The picks come from a sample history. The text is exactly what the CLI prints.

Every pick has a receipt. No "because you starred X": the seen in line points at the session where the need showed up and quotes what you said. If repofit cannot point at your history, it does not make the pick.

The list at the bottom matters more than it sounds. Every skill and MCP server you installed and forgot still costs context on every single request, and repofit names the ones none of your sessions ever called.

How it picks

[How repofit picks, as a sketch. Read memory files, rules and your own messages from every agent on your machine. Write a one-page profile where every line cites the chat it came from. Retrieve 30 of 18,338 repositories. Rank what you most likely do not know yet, crossing out what you already know.]

Each agent stores its history differently, and the formats change every few months, so repofit ships one adapter per agent. The profile is written from a redacted, numbered evidence pack, and any claim that cites evidence that does not exist is thrown out by the code, not left to the model's good manners. Retrieval runs one query per task you actually do, with project names and search phrases the model adds, so it finds the library a task depends on even when you never typed its name. The ranker is told to skip the household names you already know. The candidate pool is rebuilt every Monday from the GitHub API: active repositories above 3,000 stars, new ones above 1,000, the agent ecosystem above 300, plus GitHub trending.

Your history stays yours

  • Everything runs on your machine. repofit reads the files your agents already keep and writes its own to ~/.repofit.
  • You choose the depth: installed tools only, plus memory and instruction files (the default), or plus your own messages and tool calls.
  • Before any model sees a line, API keys, tokens, passwords, emails, phone numbers and random-looking strings (yes, including the password you once pasted after ssh) are stripped, and your home folder becomes ~.
  • With MCP, the text goes to the model your agent already uses. From the command line it goes only to the provider you name, after you confirm.
  • Your notes and other people's READMEs can hide instructions. repofit hands everything over as data, and the agent is told never to follow what it finds inside.

Supported agents

AgentSessionsMemory and instructionsInstalled tools
Claude CodeyesCLAUDE.md, project memoryskills, plugins, MCP servers
Codexyes, CLI and desktopAGENTS.md, memories/skills, plugins, MCP servers
Cursoryesuser rules, pending memoriesMCP servers, extensions
Hermes AgentyesUSER.md, MEMORY.mdskills, MCP servers
Gemini CLI, Qwen CodeyesGEMINI.md, QWEN.mdMCP servers, extensions
Cline, Roo Code, Kilo Codeyes.clinerulesMCP servers
Continueyesrules/MCP servers
VS Code Copilotyescopilot-instructions.mdMCP servers, extensions
Kimi CLI, Aideryes
OpenCodecountedAGENTS.mdMCP servers
Windsurf, Claude Desktop, WorkBuddy, Traeno local sessionsmemories where presentMCP servers

Project instruction files (AGENTS.md, CLAUDE.md, .cursorrules and friends) are read too. Run repofit scan to see what it finds on your machine. If your agent hides its data somewhere else, open an issue with the path and it gets an adapter.

Command line, no agent needed

Install with pipx install repofit, or put uvx in front of each command.

bash
repofit scan                                    # which agents are installed and what each one storesrepofit profile build --level L2 --provider deepseekrepofit recommend --provider deepseek --lang zh

Providers: deepseek, openai, ollama, anthropic, or any OpenAI-compatible endpoint with --provider compatible --base-url ... --model .... Keys come from DEEPSEEK_API_KEY, OPENAI_API_KEY or ANTHROPIC_API_KEY, and repofit shows how much text it will send before it sends anything.

No provider at all? Each model step prints a prompt to paste into any chat and imports the answer:

bash
repofit profile prompt --level L2 > prompt.md   # then: repofit profile apply answer.jsonrepofit profile expand --prompt                 # then: repofit profile expand --apply answer.jsonrepofit recommend --prompt --lang en            # then: repofit recommend --apply answer.jsonrepofit recommend --no-llm                      # keyword retrieval only, nothing leaves your machine

Development

bash
git clone https://github.com/pth2002/repofit && cd repofitpython -m pip install -e . pytestpython -m pytestrepofit index build      # rebuild the candidate pool yourself; needs a GitHub token

License

MIT

來源:README.md,提交 1c7c9b5

工具

10

get_evidence

Read the user's agent history

Collect what the user's local coding agents know (installed tools, memory files and, at level L2, the user's own session messages), redacted and numbered, with instructions for writing a profile. Long results come in parts.

輸入參數dayspartlevel

save_profile

Save the profile

Save the profile JSON written from get_evidence. Refs that do not exist are dropped. Returns the profile and the instructions for the search expansion.

輸入參數synthesis必填

save_expansion

Save search expansion

Save the search terms and project names written for each profile entry.

輸入參數expansion必填

show_profile

Show the profile

Show the saved profile.

無需輸入參數。

find_candidates

Find candidate repositories

Retrieve candidate GitHub repositories for the profile and return them with ranking instructions. Long results come in parts.

輸入參數toppartpoollanguage

save_recommendations

Save recommendations

Save the ranking JSON written from find_candidates. Picks that name unknown candidates or profile entries are dropped. Returns the recommendations to show the user.

輸入參數topanswer必填

show_recommendations

Show recommendations

Show the last saved recommendations.

無需輸入參數。

check_repo

Check one repository

Judge whether one GitHub repository fits the user: its facts, whether they already use it, and which profile entries it matches. Looks the repo up on GitHub if it is not indexed.

輸入參數repo必填

search_repos

Search repositories

Keyword search over the indexed GitHub repositories, leaving out what the user already uses.

輸入參數limitquery必填include_used

unused_tools

Unused installed tools

List installed MCP servers and skills that no session ever called.

無需輸入參數。

版本歷史

1
  1. v0.1.1最新Nov 3, 2026

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