Filesift

io.github.roshunsunderPublished by GitHub account roshunsunderv1.0.1Updated Oct 24, 2026

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

Overview

AI-generated overview

Lets a coding assistant index a local codebase and search it by natural-language intent using hybrid keyword and semantic search.

What you can do
FileSift indexes a local project directory and exposes four MCP tools over STDIO: filesift_search for natural-language queries, filesift_find_related for files linked by imports or semantic similarity, filesift_index to build an index, and filesift_status to check indexing progress. Search combines BM25 keyword matching with FAISS vector search via Reciprocal Rank Fusion. A background daemon keeps indexes in memory so repeat searches are fast, and indexes are stored in a .filesift directory inside each indexed project.
When to use it
Useful when an assistant needs to locate relevant code by what it does rather than by exact strings, for example finding authentication middleware or retry logic. It suits coding agents that would otherwise grep and read whole files, saving context and tokens. Best for local projects the agent already works in.
Requirements
Runs locally as a Python package installed with pip (filesift), providing the filesift-mcp command over STDIO. No accounts, API keys, or environment variables are declared. It needs local disk access to the project being indexed and enough resources to run an embedding model and daemon.
Before you install
Indexing writes a .filesift directory into each indexed project, so consider ignore patterns and version-control exclusions. The README states everything runs locally and code never leaves the machine, but the embedding model and daemon behavior should be verified before use on sensitive repositories.

Installation

In SourceWeft

  1. Open Filesift in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

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.

Source: README.md at commit 7a14f26

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v1.0.1LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts