
Local RAG MCP Server by shinpr: Setup for Claude, Cursor and Other Apps
Lets Claude, Cursor and other AI apps search your own PDF, Word, text and Markdown files, with the index kept on your computer.
This community server builds a search index of your documents on your own computer and lets your AI app search it. It reads PDF, Word, text and Markdown files from a folder you choose, and it needs no API key. The first run downloads an embedding model from Hugging Face.
After the model is cached, the project says indexing and search make no network requests unless you set an external reranker command. It is built for one local user and has no sign-in of its own.
Good for
- People with a folder of documents they want to ask questions about
- Developers who want private, offline-friendly search over project docs
- Teams that cannot send documents to a cloud search service
Works in
12 should work
Tap an app to see how to set it up and any known problems.
Supports local MCP servers.
Supports local MCP servers.
Supports local MCP servers.
Supports local MCP servers.
Supports local MCP servers.
Supports local MCP servers.
Supports local MCP servers.
Supports local MCP servers.
Supports local MCP servers.
Supports local MCP servers.
Supports local MCP servers.
Supports local MCP servers.
Client does not support this transport.
Client does not support this transport.
Install mcp-local-rag
Claude Code
- 1
Copy this prompt.
Add the mcp-local-rag server to Claude Code. Run this command: claude mcp add local-rag -e BASE_DIR=<BASE_DIR> -- npx -y mcp-local-rag Ask me for BASE_DIR and only put the values in that config, nowhere else. Then check that it loaded and tell me if I need to sign in or restart.
- 2
Paste it into Claude Code. It shows the change and asks before running it.
Requires Node.js.
Built from the package data we hold. Not yet tested by us.
Tools
Searches your indexed documents
Searches everything you have indexed by meaning and by keywords, and returns the best matching passages with their file and position. You can limit the number of results.
Try: “Find what our docs say about ERR_CONNECTION_REFUSED.”
Files ·
query_documentsReads the text around a search result
Returns the passages just before and after a search hit from the same document, so the assistant can read it in context. Two before and two after by default.
Try: “Show me the paragraphs around that result.”
Files ·
read_chunk_neighborsAdds one file to the index
Reads a PDF, Word, text or Markdown file by its full path, splits it into passages and stores them in the local index. Adding the same path again replaces the old entry.
Try: “Index /Users/me/docs/handbook.pdf.”
Write ·
ingest_fileAdds text or a web page you already have
Indexes text, Markdown or HTML that the assistant passes in, under a source name you choose. The server does not fetch web pages itself.
Try: “Index this page content under the name pricing-page.”
Write ·
ingest_dataUpdates the index to match your folders
Starts a background job that adds new and changed files, skips unchanged ones, and removes index entries for files that no longer exist on disk.
Try: “Sync my docs folder with the index.”
Delete ·
sync_startChecks on a running sync
Reports the progress of a sync job started earlier.
Try: “Is the sync finished?”
Read ·
sync_statusShows which files are indexed
Lists the supported files under your document folders and whether each one has been indexed.
Try: “Which of my documents are not indexed yet?”
Files ·
list_filesRemoves a file from the index
Deletes the stored passages of one indexed file or one text item from the local index, and reports how many passages it removed.
Try: “Remove handbook.pdf from the index.”
Delete ·
delete_fileShows index statistics
Returns how many documents and passages are indexed, memory use, uptime and the search mode.
Try: “How big is my index?”
Read ·
status
Read from the source code
Permissions
medium risk · 4 things to watch
Medium risk
The assistant can read every supported file in the folders you configure and can add or remove entries in a local search index. Point it at a folder that holds only the documents you want searchable.
What it can do
- Read your data
- Create and change things
- Delete things
- Read-only mode
Watch out for
It writes an index to disk and can remove entries
ingest and sync write the search index to the DB_PATH folder, and sync_start and delete_file remove entries from it. They do not delete your source files, so set DB_PATH to a folder you control. github.com
It reads every file in your document folders
Everything under BASE_DIR becomes searchable by the assistant. Point it at a folder with only the documents you want to share with your AI app. github.com
An optional reranker command runs on your machine
If you set RAG_RERANK_CMD, the server runs that command for each search. Leave it unset unless you wrote the command yourself. github.com
PDF figure captions download extra models
If the assistant ingests a PDF with the visual option, the server downloads a captioning model on first use: about 250 MB for the fast profile and about 1.7 GB for quality. Plain text ingestion does not need it. github.com
Security advisories
No published security advisories as of Nov 1, 2026.
Technical details
| Talks to | Hugging Face, on first run only, to download the embedding model (and the caption model if PDF figure captions are used) |
|---|---|
| Sign-in and keys | No credentials are needed. |
| Scopes |
|
Questions
Is this an official server?
No. It is a community project by shinpr and is not made by a document or AI vendor.
Do I need an API key?
No. The project needs no account or key. It does download an embedding model from Hugging Face the first time it runs.
What files can it search?
PDF, Word (DOCX), plain text and Markdown files, plus text, Markdown or HTML that your assistant passes in. Excel, PowerPoint, standalone images and source-code files are not supported.
Does my data leave my computer?
The project says indexing and search make no network requests once the model is cached, unless you set an external reranker command that does. Search results still go to your AI app, as with any tool.
What do I need installed?
Node.js 22.20 or later according to the project, and a folder of documents. The npm package's engines field asks for 22.23.4 or newer on the 22 line, so use a current 22.x. Set BASE_DIR to your folder in the install box above.
Can it delete my files?
No. Its delete tools remove entries from the search index only. Your original documents are not deleted.
Information
updated Nov 2, 2026
- Publisher
- Community
- Package
mcp-local-rag- Registry
- npm
- Transport
- stdio
- Version
- 0.23.1
- License
- MIT
- Last commit
- Oct 30, 2026
- Listed in
- Official MCP registry
Sources
Docs, issue trackers and discussions this page is built from. Issues, quotes and findings above link to their own source.
Show all 2Hide
- github.com · github.com
- github.com · github.com