Filesift

io.github.roshunsunder由 GitHub 帳號 roshunsunder 發布v1.0.1更新於 Oct 24, 2026

Local file search for AI agents — semantic + keyword indexing over your codebase.

概覽

AI 產生的概覽

讓程式助理為本機程式碼庫建立索引,並以關鍵字與語意混合搜尋依意圖尋找程式碼。

可以做什麼
FileSift 為本機專案目錄建立索引,並透過 STDIO 提供四個 MCP 工具:filesift_search 用於自然語言查詢,filesift_find_related 用於尋找透過匯入或語意相似度關聯的檔案,filesift_index 用於建立索引,filesift_status 用於查看索引狀態。搜尋結合 BM25 關鍵字比對與 FAISS 向量搜尋,並以 Reciprocal Rank Fusion 合併結果。背景常駐程式會將索引載入記憶體以加快重複搜尋,索引存放在每個被索引專案的 .filesift 目錄中。
適用情境
適合助理需要依程式碼功能而非精確字串定位相關程式碼的情境,例如尋找驗證中介層或重試邏輯。適用於原本需要 grep 並讀完整個檔案的程式助理,可節省上下文與 token。最適合助理已在其中工作的本機專案。
執行需求
以本機 Python 套件形式執行,透過 pip 安裝 filesift,提供 STDIO 方式的 filesift-mcp 命令。未宣告帳號、API 金鑰或環境變數。需要存取被索引專案的本機磁碟,並具備執行嵌入模型與常駐程式的資源。
安裝前請注意
建立索引會在每個被索引專案中寫入 .filesift 目錄,建議設定忽略規則並排除版本控制。README 稱全部在本機執行、程式碼不會離開本機,但在敏感程式碼庫上使用前應確認嵌入模型與常駐程式的行為。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Filesift,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

[FileSift]

FileSift

A local, open-source utility that helps AI coding agents intelligently search and understand codebases.

[PyPI] [Python]


FileSift lets your AI coding agent search across a codebase based on what code does, rather than what it looks like. Instead of sifting through entire files after a grep, your agent can jump straight to the most relevant code using natural language queries like "authentication middleware" or "database connection pooling". Everything runs locally on your machine — your code never leaves your environment.

Key benefits:

  • Smarter search — hybrid keyword + semantic search finds code by intent, not just string matching
  • Less context wasted — agents get pointed to the right files immediately, saving token budget on exploration

Installation

bash
pip install filesift

Usage

There are three ways to use FileSift, depending on your workflow:

1. CLI

The most straightforward approach. Good for testing queries, managing indexes, and configuring settings.

bash
# Index a projectfilesift index /path/to/your/project
# Search for files by what they dofilesift find "authentication and session handling"
# Search in a specific directoryfilesift find "retry logic for API calls" --path /path/to/project

2. MCP Server

Installing FileSift also provides a filesift-mcp command — a lightweight MCP server that exposes indexing and search as tools over STDIO. This works with most popular coding agents including Claude Code, Cursor, Copilot, and more.

Add it to your agent's MCP configuration:

json
{  "mcpServers": {    "filesift": {      "command": "filesift-mcp"    }  }}

The MCP server exposes four tools:

  • filesift_search — search an indexed codebase by natural language query
  • filesift_find_related — find files related to a given file via imports and semantic similarity
  • filesift_index — index a directory to enable searching
  • filesift_status — check indexing status of a directory

3. Skills

FileSift ships with a search-codebase skill that can be installed directly into your coding agent's skill directory. This lets the agent interact with the FileSift CLI through bash, without requiring MCP support.

bash
# Install for Claude Code (default)filesift skill install
# Install for other agentsfilesift skill install --agent cursorfilesift skill install --agent copilotfilesift skill install --agent codex

Supported agents: claude, codex, cursor, copilot, gemini, roo, windsurf.

How It Works

FileSift uses a daemonized embedding model to keep searches fast. At its core, it generates embeddings from code descriptions and performs searches against small vector stores called indexes.

  1. Indexing — filesift index first builds a fast keyword/structural index (completes in seconds), then triggers background semantic indexing that generates embeddings for each file.

  2. Daemon — A background daemon loads indexes into memory and automatically shuts down after a configurable period of inactivity. After the first cold-start search, subsequent searches are near-instant.

  3. Search — Queries are matched using both keyword (BM25) and semantic (FAISS) search, then combined via Reciprocal Rank Fusion for the best of both approaches.

Indexes are stored in a .filesift directory within each indexed project.

Configuration

FileSift uses a TOML configuration file, manageable via the CLI:

bash
# View all settingsfilesift config list --all
# Set a valuefilesift config set search.MAX_RESULTS 20filesift config set daemon.INACTIVITY_TIMEOUT 600
# Manage ignore patternsfilesift config add-ignore "node_modules" ".venv"filesift config list-ignore

Configuration sections: search, indexing, daemon, models, paths.

Contributing

Contributions are welcome! To get started:

bash
git clone https://github.com/roshunsunder/filesift.gitcd filesiftpip install -e .
  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/my-feature)
  3. Commit your changes and open a pull request

License

Apache 2.0 — see LICENSE for details.

來源:README.md,提交 7a14f26

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v1.0.1最新Sep 16, 2026

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