About Agentic RAG With MCP Server
Agentic RAG With MCP Server is an MCP server published by ashishpatel26 in the AI category: agentic RAG with MCP Server.
The repository has 35 stars and 10 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/ashishpatel26/Agentic-RAG-with-MCP-ServerThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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README
🚀 Agentic RAG with MCP Server 
✨ Overview
Agentic RAG with MCP Server is a powerful project that brings together an MCP (Model Context Protocol) server and client for building Agentic RAG (Retrieval-Augmented Generation) applications.
This setup empowers your RAG system with advanced tools such as:
- 🕵️♂️ Entity Extraction
- 🔍 Query Refinement
- ✅ Relevance Checking
The server hosts these intelligent tools, while the client shows how to seamlessly connect and utilize them.
🖥️ Server — server.py
Powered by the FastMCP class from the mcp library, the server exposes these handy tools:
| Tool Name | Description | Icon |
|---|---|---|
get_time_with_prefix |
Returns the current date & time | ⏰ |
extract_entities_tool |
Uses OpenAI to extract entities from a query — enhancing document retrieval relevance | 🧠 |
refine_query_tool |
Improves the quality of user queries with OpenAI-powered refinement | ✨ |
check_relevance |
Filters out irrelevant content by checking chunk relevance with an LLM | ✅ |
🤝 Client — mcp-client.py
The client demonstrates how to connect and interact with the MCP server:
- Establish a connection with
ClientSessionfrom themcplibrary - List all available server tools
- Call any tool with custom arguments
- Process queries leveraging OpenAI or Gemini and MCP tools in tandem
⚙️ Requirements
- Python 3.9 or higher
openaiPython packagemcplibrarypython-dotenvfor environment variable management
🛠️ Installation Guide
# Step 1: Clone the repository
git clone https://github.com/ashishpatel26/Agentic-RAG-with-MCP-Server.git
# Step 2: Navigate into the project directory
cd Agentic-RAG-with-MCP-Serve
# Step 3: Install dependencies
pip install -r requirements.txt
🔐 Configuration
- Create a
.envfile (use.env.sampleas a template) - Set your OpenAI model in
.env:
OPENAI_MODEL_NAME="your-model-name-here"
GEMINI_API_KEY="your-model-name-here"
🚀 How to Use
- Start the MCP server:
python server.py
- Run the MCP client:
python mcp-client.py
📜 License
This project is licensed under the MIT License.
Thanks for Reading 🙏
README fetched from the repository 6 hours ago. The original is authoritative.