Mcp App
What is Mcp App
mcp-app is a server application designed for managing and enhancing knowledge retrieval using Retrieval-Augmented Generation (RAG) tools and web searching capabilities.
Use cases
Use cases for mcp-app include building intelligent applications that require dynamic knowledge retrieval, enhancing chatbots with up-to-date information, and integrating document management systems with advanced search functionalities.
How to use
To use mcp-app, set up your environment by running ‘uv sync’, activate the virtual environment with ‘source .venv/bin/activate’, and start the application with ‘mcp dev run’.
Key features
Key features include integration with SQLAlchemy for database interactions, support for PostgreSQL as the SQL database, and the use of OpenAI for vectorstore embeddings, allowing for efficient knowledge retrieval and document augmentation.
Where to use
mcp-app can be utilized in fields such as data management, artificial intelligence, and any domain requiring enhanced knowledge retrieval and processing capabilities.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Mcp App
mcp-app is a server application designed for managing and enhancing knowledge retrieval using Retrieval-Augmented Generation (RAG) tools and web searching capabilities.
Use cases
Use cases for mcp-app include building intelligent applications that require dynamic knowledge retrieval, enhancing chatbots with up-to-date information, and integrating document management systems with advanced search functionalities.
How to use
To use mcp-app, set up your environment by running ‘uv sync’, activate the virtual environment with ‘source .venv/bin/activate’, and start the application with ‘mcp dev run’.
Key features
Key features include integration with SQLAlchemy for database interactions, support for PostgreSQL as the SQL database, and the use of OpenAI for vectorstore embeddings, allowing for efficient knowledge retrieval and document augmentation.
Where to use
mcp-app can be utilized in fields such as data management, artificial intelligence, and any domain requiring enhanced knowledge retrieval and processing capabilities.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
MCP APP
This repository serves an MCP application with RAG and Web Searching tools.
RAG tools let LLM not only retrieve knowledge from vectorstore but add documents, augmenting size of knowledge that LLM uses.
Technology stack
- ⚙️ MCP Server Application for implementation of MCP server.
- 🧰 SQLAlchemy for the SQL database interaction (ORM)
- 🤖 OpenAI for the embedding of vectorstore.
- 💾 PostgreSQL as the SQL database.
- 🦜 PGVector as vectorstore.
QuickStart
uv sync
source .venv/bin/activate
mcp dev run
Combining Claude Desktop with MCP APP
# You must install all dependencies written in pyproject.toml
mcp install server.py --env-file .env --with sqlalchemy --with pgvector --with openai --with "psycopg[binary]" --with pydantic --with python-dotenv --with tavily-python
Preview of Claude Desktop
TODO
- Make asynchronous implementations.
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
