Localsynapse

Created By
LocalSynapse2 months ago
Offline AI-powered local file search MCP server for Windows. Searches inside document contents (Word, Excel, PDF, PowerPoint, HWP) using BM25 + dense vector hybrid search. 100% local, no cloud, no login, no telemetry.
Overview

LocalSynapse

Local file search engine with MCP server. Indexes files across all drives and provides full-text search, filename search, and semantic search — all running 100% offline.

Features

  • File scanning — Indexes all fixed drives, skips cloud placeholders (OneDrive, Dropbox, etc.)
  • Full-text search — BM25 ranking with Porter stemmer, Korean/English support
  • Semantic search — BGE-M3 embedding model (optional, runs locally via ONNX)
  • MCP server — stdio JSON-RPC server for AI assistant integration
  • Desktop UI — Avalonia cross-platform GUI

Build

dotnet build LocalSynapse.v2.sln

Run

# GUI
dotnet run --project src/LocalSynapse.UI

# MCP server
dotnet run --project src/LocalSynapse.UI -- mcp

Project Structure

src/
  LocalSynapse.Core/       # Models, Interfaces, DB
  LocalSynapse.Pipeline/   # Scan, parse, chunk, embed
  LocalSynapse.Search/     # BM25, Dense, Hybrid search
  LocalSynapse.Mcp/        # MCP stdio server
  LocalSynapse.UI/         # Avalonia desktop app

MCP Configuration

Add LocalSynapse as an MCP server in your Claude Desktop or Claude Code config:

{
  "mcpServers": {
    "localsynapse": {
      "command": "C:\\Program Files\\LocalSynapse\\LocalSynapse.exe",
      "args": ["mcp"],
      "env": {}
    }
  }
}

Available MCP Tools

ToolDescription
search_filesSearch files by keyword or semantic query
get_file_contentRead the content of an indexed file
list_indexed_filesList all indexed files with filters
get_pipeline_statusCheck indexing pipeline status

License

Apache License 2.0

Code Signing Policy

LocalSynapse releases are signed to ensure authenticity and integrity.

Free code signing provided by SignPath.io, certificate by SignPath Foundation.

Team Roles

Privacy Policy

This program will not transfer any information to other networked systems unless specifically requested by the user or the person installing or operating it.

All file indexing, search, and AI embedding operations run 100% locally on your machine. No data is sent to any external server. No login or account is required.

Server Config

{
  "mcpServers": {
    "localsynapse": {
      "command": "path/to/LocalSynapse.exe",
      "args": [
        "mcp"
      ]
    }
  }
}
Project Info
Created At
2 months ago
Updated At
2 months ago
Author Name
LocalSynapse
Star
-
Language
-
License
-
Category

Recommend Servers

View All
Docwand

14 hours ago
//beforeyouship — LLM Cost Modeling From Your Editor
@Indiegoing

Query realistic LLM cost models without leaving your editor. beforeyouship models the **true monthly cost** of an LLM app architecture — retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth — across GPT-5.x, Claude, Gemini, DeepSeek, and more. Not a token calculator: a planning tool for the design phase, before you commit to a stack. **No API key needed to try it** — demo mode covers the six free-tier models. A Pro key from [beforeyouship.dev](https://beforeyouship.dev) unlocks the full 18-model catalog. ## What you can ask - "How much will a RAG chatbot cost at 10,000 requests/day?" - "Compare Claude Haiku vs Gemini Flash pricing for my workload" - "What's the cheapest model for a multi-step agent at scale?" - "Show me current per-token prices for Anthropic models" ## Tools ### `estimate_cost` Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case monthly cost per model, 3×/10× growth scenarios, and an opinionated recommendation with reasoning. ### `get_model_prices` Current per-1M-token pricing — input, output, cached input, batch — with context windows and staleness metadata. ### `list_archetypes` Seven preset architecture patterns (simple chatbot, chatbot with history, RAG pipeline, multi-model router, coding assistant, document processor, multi-step agent) used as starting points for estimates. ## Setup **Claude Code:** ​```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ​``` **Cursor / other clients** — add a remote server: ​```json { "mcpServers": { "beforeyouship": { "type": "streamable-http", "url": "https://beforeyouship.dev/api/mcp" } } } ​``` Add an `Authorization: Bearer bys_...` header with a Pro key for the full catalog. ## Try it > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day

14 hours ago