Mmcp.market

Local Rag MCP server

by shinpr·io.github.shinpr/mcp-local-rag·v0.18.6

Easy-to-setup local RAG server with minimal configuration

A92/100grade A
What users say
No reviews yet
Be the first
Safety scan
A92/100

full report

Adoption
Established

400 stars4.8k downloads/wk

Reviews

Write one

Nobody has reviewed Local Rag yet.

If you have run it, two minutes of your experience saves the next person an afternoon.

Local Rag tools (9, 1 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • delete_filewrite action

    Delete a previously ingested file or data from the vector database. Use filePath for files ingested via ingest_file, or source for data ingested via ingest_data. Either filePath or source must be provided. Returns deleted (operation succeeded), removedChunks, and existed (whether anything was actually present).

  • ingest_data

    Ingest in-memory content as a string (use ingest_file for files on disk). The source identifier enables re-ingestion to update existing content. Returns { filePath, chunkCount, timestamp, fileTitle }.

  • ingest_file

    Ingest a document file (PDF, DOCX, TXT, MD) into the vector database. Path must be absolute; re-ingesting the same path replaces its existing data. Returns { filePath, chunkCount, timestamp, fileTitle }.

  • list_files

    List supported files (PDF, DOCX, TXT, MD) under the configured base directories and whether each is ingested. Returns { baseDirs, files, sources }; sources lists ingested items reported apart from the file scan, chiefly ingest_data content (web pages, clipboard, etc.).

  • query_documents

    Search ingested documents with hybrid keyword + semantic matching. Returns results sorted by relevance, each with filePath, chunkIndex, text, fileTitle, score (0 = best, higher = worse), and source (for ingest_data items).

  • read_chunk_neighbors

    Read the chunks immediately before and after a query_documents result, in the same document, for more surrounding context. Pass chunkIndex from the result plus exactly one of filePath (ingest_file) or source (ingest_data). Returns the target chunk (isTarget: true) and its neighbors, ascending by chunkIndex; an out-of-range chunkIndex returns []. Defaults: before=2, after=2 (max … each).

  • status

    Get index status: { documentCount, chunkCount, memoryUsage (MB), uptime (s), ftsIndexEnabled, searchMode }.

  • sync_start

    Reconcile the index with the files on disk: ingest new and changed files, leave unchanged files alone, and remove index entries for files that are gone. Each changed PDF is re-ingested with the visual profile ("fast" or "quality") already recorded for it, so a PDF indexed with VLM captions keeps them; a PDF with no recorded profile stays text-only. There is no option to change a profile here — use

  • sync_status

    Get the current or latest sync job record: { jobId, state ("running" | "succeeded" | "failed"), total (null until scanning has counted the files on disk), completed (upserted + skipped + empty; pruned is counted separately), summary { upserted, skipped, empty, pruned }, warnings, error (null unless the job failed) }. An unknown jobId means the job was replaced by a newer one or lost with a previou

Public scan report

scanner v0.1.5 · 2026-09-19 · same rubric, same numbers if you re-run it

no findings
  • Code scan117 source files scanned25/25
  • Live reliabilityno gateway calls yet and no remote to proben/a
  • Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 2 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 92/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

Install directly

Runs npx -y mcp-local-rag on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add mcp-local-rag -- npx -y mcp-local-rag
Add to Cursor

Local Rag: common questions

Is Local Rag MCP server safe?
Yes, by our scan: it is graded A (92/100). Read the Local Rag safety report
How do I install Local Rag?
It runs on your machine. Copy the Claude Code, Claude Desktop or Cursor config from the install section.
Does Local Rag need an API key?
No secret keys are declared. It reads 15 settings from the environment.
Is Local Rag maintained?
The last commit was 2 days ago (2026-09-18). The latest release is v0.18.6.
What can I use instead of Local Rag?
Servers from other publishers that do the same job: Agent-Native Chat MCP server, Google Surf MCP server and PDF MCP server. Compare all Local Rag alternatives.

Alternatives to Local Rag

Same job from other publishers: the closest match first, then the best rated.

All Local Rag alternatives →
  • Agent-Native Chat
    Minimal chat-first app with durable threads, actions, and the app-agent loop
    A
  • Google Surf
    Web, academic and code search with graph RAG, data lineage, ontology and cross-project schema links.
    B
  • PDF
    Agentic RAG over one PDF or a whole folder: hybrid search, selective page reads, tables, OCR.
    A
  • haiku.rag
    Local-first agentic RAG with citations - hybrid search, reranking, multimodal document retrieval
    A
  • rag-rat
    Repository intelligence, code graph, history, papertrail, and cross-agent memory for coding agents.
    B

More from shinpr