jerry-ai-dev/MODULAR-RAG-MCP-SERVER
A modular RAG (Retrieval-Augmented Generation) system with MCP Server architecture. Using Skill to make AI follow each step of the spec and complete the code 100% by AI. observed · 2026-08-28
Health v2 · maintenance only
47/100
- Activity 71
- Release rhythm 35
- Longevity 16
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 225
- days_rel: n/a
- days_push: 176
- n_releases_24m: 0
Adoption not part of the score
1109 stars · 253 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A modular, pluggable RAG (Retrieval-Augmented Generation) framework exposed as an MCP (Model Context Protocol) server, so AI assistants like Copilot and Claude Desktop can query a knowledge base directly. It includes a full ingestion pipeline (PDF to embeddings), hybrid search with reranking, multimodal image captioning, Ragas-based evaluation, a Streamlit dashboard, and doubles as a hands-on learning project for LLM engineering job seekers.
Use cases
- expose a document knowledge base to Claude Desktop or Copilot via MCP
- build a RAG pipeline over PDFs with hybrid BM25 and dense vector search
- add reranking with cross-encoders or LLM rerankers to retrieval
- make images searchable by captioning them with a vision LLM
- evaluate RAG quality with Ragas and golden test sets
- trace ingestion and query pipelines end to end
- learn RAG engineering for LLM job interviews
- swap LLM, embedding, reranker, or vector store backends via config
When to choose
- you want a working MCP-accessible RAG server with pluggable components
- you need hybrid search plus reranking out of the box
- you want a complete, observable RAG reference implementation to study or extend
- you are preparing for LLM/RAG engineering interviews and want a portfolio project
When to avoid
- you need a production-hardened, licensed product (no license is provided)
- you want a simple drop-in library rather than a full server with dashboard and pipelines
- you need non-Python runtimes or managed cloud deployment
- you require guaranteed long-term maintenance or enterprise support
Facets
service · maturity active
rag search-engine mcp llm-inference pdf data-visualization monitoring machine-learning large-language-models artificial-intelligence developer-tools tutorials python self-hosted mcp-server hybrid-search rerank bm25 vector-search image-captioning ragas-evaluation streamlit-dashboard skill-driven-development interview-preparation pluggable-architecture retrieval-augmented-generation natural-language-processing search docker web-server
1 source
- readme: https://github.com/jerry-ai-dev/MODULAR-RAG-MCP-SERVER · fetched 2026-08-28 · 03edc17cd11a
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| jerry-ai-dev/MODULAR-RAG-MCP-SERVER | main | 47 |
For agents
markdown · JSON · MCP: product_card(name="jerry-ai-dev/MODULAR-RAG-MCP-SERVER")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem