MCP.Market

Rag Vault MCP server

by RobThePCGuy·io.github.RobThePCGuy/rag-vault·v1.5.3·2 stars
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Local RAG MCP server with hybrid search, PDF/DOCX support, and zero-config setup

A92/100grade A
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Safety scan
A92/100

full report

Adoption
Growing

2 stars

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

Rag Vault 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.

  • feedback_dismiss

    Dismiss a search result as irrelevant for a query. Dismissed results will be penalized in future searches. Use when a result was unhelpful.

  • feedback_pin

    Pin a search result as relevant for a query. Pinned results will be boosted in future searches. Use when a result was particularly helpful.

  • feedback_stats

    Get feedback statistics including total events, pinned pairs, and dismissed pairs.

  • ingest_data

    Ingest content as a string, not from a file. Use for: fetched web pages (format: html), copied text (format: text), or markdown strings (format: markdown). The source identifier enables re-ingestion to update existing content. Optional custom metadata can include author, domain, tags, etc. For files on disk, use ingest_file instead.

  • ingest_file

    Ingest a document file (PDF, DOCX, TXT, MD, JSON, JSONL) into the vector database for semantic search. File path must be an absolute path. Supports re-ingestion to update existing documents. Optional metadata can include author, domain, tags, etc.

  • list_files

    List all ingested files in the vector database. Returns file paths and chunk counts for each document.

  • query_documents

    Search ingested documents using hybrid semantic + keyword search. Advanced syntax supported: - "exact phrase" → Match phrase exactly - field:value → Filter by custom metadata (e.g., domain:legal, author:john) - term1 AND term2 → Both terms required (default) - term1 OR term2 → Either term matches - -term → Exclude results containing term Results include score (0 = most relevant, higher = less rele

  • status

    Get system status including total documents, total chunks, database size, and configuration information.

Public scan report

scanner v0.1.10 · 2026-09-28 · same rubric, same numbers if you re-run it

no findings
  • Code scan76 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 7 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

How Rag Vault compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
92/100
higher than 90% of 4,460 AI and agents servers
Tools
9
the typical AI and agents server has 6
Tools that change things
11%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
2
more than 65% of 2,711 AI and agents servers

What its tools let an agent do: 8 read · 1 delete

Install Rag Vault in Claude Code, Cursor or VS Code

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

claude mcp add rag-vault -- npx -y @robthepcguy/rag-vault
Add to Cursor

What the publisher says

From the Rag Vault repository's README, as published. We do not edit it. Read it on GitHub

RAG Vault

Your documents. Your machine. Your control.

RAG Vault lets your AI coding assistant search your private documents, things like API specs, research papers, and internal docs. Everything runs locally and your data stays on your machine unless you choose to pull in content from a remote URL.

One command to run, minimal setup, privacy by default.

Why RAG Vault?

Security

RAG Vault comes with security built in:

  • API Authentication: Optional API key via RAGAPIKEY
  • Rate Limiting: You can throttle requests
  • CORS Control: Restrict allowed origins
  • Security Headers: Helmet.js protection

See SECURITY.md for complete documentation.

First-Time Setup Checklist

Before adding MCP config:

  1. Install Node.js 20 or newer.
  2. Pick a documents directory and set BASE_DIR to that path.
  3. Make sure your AI tool process can read BASE_DIR.
  4. Restart your AI tool after editing config.

Get Started Quickly

For Cursor

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "local-rag": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "github:RobThePCGuy/rag-vault"],
      "env": {
        "BASE_DIR": "/path/to/your/documents"
      }
    }
  }
}

Replace /path/to/your/documents with your real absolute path.

For Claude Code

Add to .mcp.json in your project directory:

{
  "mcpServers": {
    "local-rag": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "github:RobThePCGuy/rag-vault"],
      "env": {
        "BASE_DIR": "./documents",
        "DB_PATH": "./documents/.rag-db",
        "CACHE_DIR": "./.cache",
        "RAG_EMBEDDING_DEVICE": "cpu",
        "RAG_HYBRID_WEIGHT": "0.6",
        "RAG_GROUPING": "related"
      }
    }
  }
}

Or add inline via CLI:

claude mcp add local-rag --scope user --env BASE_DIR=/path/to/your/documents -- npx -y github:RobThePCGuy/rag-vault

For Codex

Add to ~/.codex/config.toml:

[mcp_servers.local-rag]
command = "npx"
args = ["-y", "github:RobThePCGuy/rag-vault"]

[mcp_servers.local-rag.env]
BASE_DIR = "/path/to/your/documents"

Install Skills (Optional)

If you want your AI to write better queries and make more sense of results, install the RAG Vault skills:

# Claude Code (project-level - recommended for team projects)
npx github:RobThePCGuy/rag-vault skills install --claude-code

# Claude Code (user-level - available in all projects)
npx github:RobThePCGuy/rag-vault skills install --claude-code --global

# Codex (user-level)
npx github:RobThePCGuy/rag-vault skills install --codex

# Custom location
npx github:RobThePCGuy/rag-vault skills install --path /your/custom/path

Skills teach Claude best practices for:

  • Query formulation and expansion strategies
  • Score interpretation. In boost mode, under 0.3 is a good match and over 0.5 is worth skipping. RRF mode scores by rank instead.
  • When to use ingestfile vs ingestdata
  • HTML ingestion and URL handling

Restart your AI tool, and start talking:

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Rag Vault: common questions

Is Rag Vault MCP server safe?
Yes, by our scan: it is graded A (92/100). Read the Rag Vault safety report
How do I install Rag Vault?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Rag Vault need an API key?
No secret keys are declared. It reads 6 settings from the environment.
Is Rag Vault maintained?
The last commit was 44 days ago (2026-09-21). The latest release is v1.5.3.
What can I use instead of Rag Vault?
Servers from other publishers that do the same job: PDF MCP server, Local Rag MCP server and Butterbase AI MCP server.
How does Rag Vault compare with other AI and agents MCP servers?
safety score 92/100 (higher than 90% of 4,460 AI and agents servers); tools 9 (the typical AI and agents server has 6); tools that change things 11% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to Rag Vault

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

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