MCPverse

🚀 MCPverse

MCPverse is a semantic search engine for discovering Model Configuration Protocol (MCP) servers across GitHub. It indexes public MCP repositories and enables powerful natural language search using vector embeddings and OpenSearch.

---

📡 Live Demo

Try out the hosted version of MCPverse here:
👉 https://mcpverse.streamlit.app

---

✨ Features

• 🔍 Semantic search using OpenAI embeddings (text-embedding-ada-002)
• 📚 Indexes name, description, and README content
• ⚙️ Client configuration preview (where available)
• 🎨 Interactive UI using Streamlit

---

📦 Project Structure

.
├── backend
│   ├── fetch_repos.py      # Get MCP server repos from Github
│   ├── extract_config.py   # Logic to extract MCP client config from README
│   ├── embedder.py         # OpenAI + OpenSearch indexing and search logic
|   ├── github_scraper.py   # Using Github API to search on MCP servers 
│   └── data/
│       └── mcpverse_data.json  
├── frontend
│   └── app.py               # Streamlit app
├── requirements.txt
├── README.md
├── .env
├── .gitignore

---

🛠️ Local Setup Guide

1. Clone the Repository

git clone https://github.com/Harika-BV/MCPverse.git
cd MCPverse

---

2. Set Up Python Environment

python -m venv venv
source venv/bin/activate  # For Windows: venv\Scripts\activate
pip install -r requirements.txt

---

3. Configure Environment Variables

Create a .env file in the root:

GH_API_KEY=your-github-token
ENV=local
OPENAI_API_KEY=your-openai-key
OPENSEARCH_HOST=localhost
OPENSEARCH_PORT=9200
OPENSEARCH_USER=admin
OPENSEARCH_PASS=admin

💡 You can also connect to your hosted OpenSearch or Elasticsearch cluster.

---

4. Start OpenSearch Locally (Optional)

If you're running OpenSearch locally, use Docker:

docker run -d --name opensearch -p 9200:9200 \
  -e "discovery.type=single-node" \
  -e "plugins.security.disabled=true" \
  opensearchproject/opensearch:2.11.1

---

5. Index MCP Repositories

cd backend
python embedder.py

This will:

• Load the GitHub MCP repo data (from mcpverse_data.json)
• Generate OpenAI embeddings
• Index them into OpenSearch

---

6. Run the Streamlit App

cd frontend
streamlit run app.py

Then open http://localhost:8501 in your browser.

---

🧑‍💻 Maintainer

Built with ❤️ by Harika B V

---

⚠️ Disclaimer

All repositories and data are publicly available on GitHub.
MCPverse is a community project and is not affiliated with any third-party MCP maintainers.