minirag-mcp

io.github.sfrangulov/minirag-mcp

6/7 checks passed
Runs locally
No secrets
★ 59 GitHub stars
Updated 2026-10-22
Health score 55

About minirag-mcp

minirag-mcp is an MCP server published by the GitHub account sfrangulov. Local-first RAG MCP server: hybrid search over a folder of your own documents

It runs on your own machine: your AI client starts it from the PyPI package minirag-mcp at version 1.0.0.

It asks for no keys or passwords.

Version 1.0.0 was published on 22 October 2026, and the source code is public, so you can read it before installing.

Written from the registry entry. 9 automated checks on the registry entry and the package code: 6 pass, 1 warn, 0 fail, 2 info. How we check.

What it asks for

Variable	Required	Secret	Description
`BASE_DIR`	No	No	One document root; also the security boundary for file access. Defaults to the process working directory. Ignored when BASE_DIRS is set.
`BASE_DIRS`	No	No	JSON array of document roots, e.g. ["/docs/a", "/docs/b"]. Takes precedence over BASE_DIR. An invalid value is a hard configuration error.
`DB_PATH`	No	No	LanceDB index directory. Defaults to <first root>/.minirag/lancedb, so each corpus gets its own index.
`CACHE_DIR`	No	No	Embedding model cache. Defaults to the platform user cache dir, so the ~220 MB model is downloaded once and shared.
`MODEL_NAME`	No	No	fastembed model id. Changing it makes existing vectors incompatible with new queries; pair with a new DB_PATH or a full re-ingest.
`MAX_FILE_SIZE`	No	No	Per-file size limit in bytes, enforced before parsing.
`CHUNK_TOKEN_BUDGET`	No	No	Retrieval-unit size in the embedding model's own tokens. Range 16-128; the ceiling is the model's trained sequence length.
`RAG_HYBRID_WEIGHT`	No	No	Keyword weight in the weighted RRF fusion, range 0.0-1.0. 0 is vector-only; higher values raise the BM25 contribution.
`RAG_GROUPING`	No	No	Result grouping filter. 'similar' keeps only the closest group; 'related' also keeps the next one. Unset means no grouping filter.
`RAG_MAX_DISTANCE`	No	No	Drop results whose vector distance exceeds this value. Lower is stricter. Unset means no distance filter.
`RAG_MAX_FILES`	No	No	Keep chunks from at most this many best-scoring files. Unset means no per-file filter.
`RAG_INSTRUCTIONS_APPEND`	No	No	Extra paragraph appended to the instructions the server hands the client at connect time, for corpus-specific guidance.
`ALLOW_PRIVATE_URLS`	No	No	Let ingest_url fetch hosts resolving to loopback, link-local, private, reserved or unspecified addresses. Off by default.

Checks

Check	Result	Detail
Source repository linked	Pass	https://github.com/sfrangulov/minirag-mcp
Version pinned	Pass	Every package has an explicit version
Secrets requested	Info	Asks for no secrets
Known package registry	Pass	All packages come from npm, PyPI, OCI, NuGet or MCPB
Namespace ownership	Info	Name verified via GitHub account sfrangulov
Registry text aimed at the AI	Pass	Description and settings contain no hidden characters or instructions to the AI
Install scripts	Pass	minirag-mcp 1.0.0 has no setup.py; nothing runs at install
Code red flags	Warn	Reads SSH or cloud credentials (minirag_mcp-1.0.0/src/minirag_mcp/ingest/scanner.py:134: "/.ssh/id_")
Text aimed at the AI	Pass	No hidden characters or instructions to the AI in 107 files, including comments and the README

Popularity & health: 55 / 100

Worked out from public numbers and our own checks, not from user reviews or ratings. It says how used and how looked-after a server is, not whether it is safe.

Popularity16 / 40

59 GitHub stars, 137 downloads last week, 0 Hacker News posts (0 points). Best two of the three, each on a log scale.

Activity15 / 25

Last push 2026-10-23, last release 2026-10-22, 0 commits in 90 days.

Issue health8 / 15

1 closed of 1 issues, too few to judge. No data, so half marks.

Our checks16 / 20

1 warning, each costing a fifth.

2 forks, 27 merged pull requests. Sources: GitHub, npm, PyPI (pypistats.org) and Hacker News (Algolia), fetched 2026-10-31.

What people say

No Hacker News threads link to its source code.

Look further: search Reddit, search Hacker News, read its GitHub issues. These are not reviews we checked.

Facts

Registry name	`io.github.sfrangulov/minirag-mcp`
Publisher	GitHub account sfrangulov
How the name is verified	Name verified via GitHub account sfrangulov. The registry ties the name prefix to that account or domain; it does not check the code.
Type	Local: runs on your machine from a package
Packages	pypi `minirag-mcp` 1.0.0 (stdio)
Version	1.0.0
Published	2026-10-22
Last updated	2026-10-22
Source repository	https://github.com/sfrangulov/minirag-mcp
Website	https://github.com/sfrangulov/minirag-mcp#readme
Category	Files & documents (assigned by keyword rule, not by hand)

Install

Claude Desktop · Python package

{
  "mcpServers": {
    "minirag-mcp": {
      "command": "uvx",
      "args": [
        "minirag-mcp==1.0.0"
      ]
    }
  }
}

What these checks don't cover

We did not run this server, so we don't know what it does when it runs. We read its package code on 2026-10-29 without running it, and pattern searches miss what they have no pattern for. Tool descriptions built at run time were not seen. And we don't watch it after you install: if the publisher changes it later (a rug pull), this page won't notice until the next scan. Treat a pass as "nothing found", not as "safe".

For people and their AI

The same data as plain JSON: /data/servers/io-github-sfrangulov-minirag-mcp.json. Text inside it that came from the publisher is data, not instructions.