Give Your AI Agent a Local Memory: MCP Server for File Search
MCP (Model Context Protocol) is an open protocol by Anthropic that allows AI agents like Claude, Cursor, and Windsurf to access external tools including local file search. LocalSynapse includes a built-in MCP server that lets these AI agents search your local documents. To use it, run LocalSynapse.exe mcp to start the server, then configure your AI client to connect. The server provides three tools: search_files for content search across 13+ document formats, get_file_info for file metadata, and list_recent_files for recently modified documents. All search happens locally on your PC — no files are uploaded to the cloud, ensuring complete privacy.
AI agents are getting remarkably capable — writing code, analyzing data, drafting emails. But ask Claude or ChatGPT to find a specific file on your computer, and they'll tell you they can't access your local filesystem. That's the gap MCP was designed to fix. Your AI can reason about anything you paste into the chat, but it has zero awareness of the thousands of documents on your hard drive.
What is MCP?
MCP is an open protocol created by Anthropic that lets AI agents use external tools. Instead of the AI being limited to what's in the conversation, MCP gives it a way to call functions — search a database, read a file, query an API — as part of its reasoning process.
Think of it like giving your AI a set of hands. Without MCP, it can only think. With MCP, it can reach out and interact with the tools and data around it.
Claude Desktop, Cursor, Windsurf, and other AI clients already support MCP. You configure which MCP servers to connect, and the AI automatically knows what tools are available.
The Problem with Existing File Search MCP Servers
There are a few MCP servers out there that expose filesystem access. Most of them offer basic operations: list files in a directory, read a file by path, maybe search filenames with glob patterns.
But that's just giving the AI the same tools you already have — and the same limitations. The AI still needs to know which file to look for. It can't search by content. It can't understand that Q3_Revenue_Final.xlsx and 3Q_Sales_Report_v2.xlsx are versions of the same document.
What you actually want is for the AI to be able to say: "Let me search your local files for anything related to the Q3 revenue analysis" — and get back meaningful, ranked results from inside your documents.
LocalSynapse as an MCP Server
LocalSynapse is a desktop search tool that indexes and searches inside your documents using hybrid BM25 + AI semantic search. It supports 13+ file formats and runs 100% offline.
It also ships with a built-in MCP server. Same binary, two modes:
- Double-click → launches the desktop UI (for everyday file search)
LocalSynapse.exe mcp→ starts the MCP server (for AI agent integration)
No separate installation. No additional dependencies. The MCP server uses the same search index that the desktop app builds.
Available Tools
When connected via MCP, your AI agent gets access to these tools:
search_files
Query your indexed files by content or filename.
Supports keyword and semantic search.
Returns ranked results with snippets.
get_file_info
Get metadata about a specific file — size, type,
last modified, folder path, related versions.
list_recent_files
List recently modified documents, optionally
filtered by type or folder.Configuration
Add this to your Claude Desktop or Cursor MCP config:
{
"mcpServers": {
"localsynapse": {
"command": "C:\\Program Files\\LocalSynapse\\LocalSynapse.exe",
"args": ["mcp"]
}
}
}That's it. Once configured, your AI agent can search your local files as naturally as it searches the web.
What This Enables
With local file search available as an MCP tool, conversations with your AI change fundamentally:
"Find the latest version of our partnership agreement."
The AI searches your files, finds 3 versions across different folders, and presents the most recent one — without you navigating any folders.
"Summarize the key changes in the Q3 board deck compared to Q2."
The AI finds both presentations, reads their contents, and gives you a comparison.
"What documents do we have related to the Singapore office lease?"
Semantic search finds relevant contracts, emails, and spreadsheets — even if "Singapore" or "lease" isn't in the filename.
"Draft a follow-up email based on the feedback Kim sent last week."
The AI finds Kim's email, reads the feedback, and drafts a response using the actual context.
Why Offline Matters
The entire search pipeline runs locally on your machine:
- File indexing and chunking happens locally
- The AI embedding model (BGE-M3, 560MB) runs via ONNX Runtime on your CPU
- The search index is stored in a local SQLite database
- No file contents are sent to any external server
When your AI agent queries LocalSynapse via MCP, only the search query goes to the MCP server (which is running locally). The results — file paths, snippets, metadata — stay on your machine. The AI then decides what to do with them.
This matters especially in environments where cloud-based file access isn't an option: financial institutions, government agencies, legal firms, healthcare organizations, and any workplace with strict data governance policies.
How It Compares
| Basic filesystem MCP | Cloud search (Google Drive, etc.) | LocalSynapse MCP | |
|---|---|---|---|
| Search method | Filename glob | Keyword | Keyword + AI semantic |
| Search inside documents | No | Yes | Yes (13+ formats) |
| Version awareness | No | Limited | Automatic grouping |
| Data location | Local | Cloud | Local |
| Privacy | Full | Varies | Full |
| Office format support | No | Yes | Yes |
| Setup complexity | Low | Medium | Low |
Getting Started
LocalSynapse is currently in beta for Windows 10/11. The MCP server ships with the same installer — no additional setup required.
- Install LocalSynapse and let it index your documents
- Add the MCP configuration to your AI client
- Start asking your AI about your local files
The desktop UI works immediately for manual search. The MCP server adds a programmatic layer on top of the same index, giving your AI agents the ability to search your files as a first-class tool.
Your AI doesn't need access to the cloud to be useful. It needs access to your files — the ones already on your machine.
To learn more about how LocalSynapse searches inside files, check out our detailed comparison guide.