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minima MCP Server

Minima-AI-Inc/minima

Score: 54.6 Rank #10892 Search & RAG
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On-premises conversational RAG with configurable containers

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Overview

Minima-AI-Inc/minima is a Python tool licensed under MPL-2.0. On-premises conversational RAG with configurable containers Topics: claude, custom-gpts, docker, docker-compose, langchain, mcp, model-context-protocol, ollama, sentence-transformers, ai, huggingface, qdrant.

Ranked #10892 out of 24846 indexed tools.

Has 1,054 GitHub stars.

Has 11 contributors.

Ecosystem

Python MPL-2.0
claudecustom-gptsdockerdocker-composelangchainmcpmodel-context-protocolollamasentence-transformersaihuggingfaceqdrant

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 1,054

1,054 stars → well-known project

Freshness 25% 9mo ago

Last commit 9mo ago → stale

Issue Health 25% 42%

10/24 issues closed → many open issues

Contributors 10% 11

11 contributors → active community

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 107
Description Good
License MPL-2.0

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

How to Improve

Description low impact

Expand your description to 150+ characters for better discoverability

Freshness high impact

Last commit was 293 days ago — a recent commit would boost your freshness score

Issue Health high impact

You have 14 open vs 10 closed issues — triaging stale issues improves health

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Matched Queries

topic:mcptopic:model-context-protocol

From the README

<p align="center">
  <a href="https://mnma.ai/" target="blank"></a>
</p>

**Minima** is an open source RAG on-premises containers, with ability to integrate with ChatGPT and MCP.
Minima can also be used as a fully local RAG or with your own deployed LLM.

Minima currently supports four modes:
1. **Isolated installation (Ollama)** – Operate fully on-premises with containers, free from external dependencies such as ChatGPT or Claude. All neural networks (LLM, reranker, embedding) run on your cloud or PC, ensuring your data remains secure.

2. **Custom LLM (OpenAI-compatible API)** – Use your own deployed LLM with OpenAI-compatible API (vLLM, Ollama server, TGI, etc.). The indexer runs locally while the LLM can be on your server, cloud, or local machine. No Ollama deployment needed, lighter resource usage, and full control over your LLM infrastructure.

3. **Custom GPT** – Query your local documents using ChatGPT app or web with custom GPTs. The indexer runs on your cloud or local PC, whi
Read full README on GitHub →

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