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Agentic RAG With MCP Server 1

by · github.com/iflow-mcp/Agentic-RAG-with-MCP-Server-1

Agentic RAG with MCP Server

Unclaimed last commit 10 months ago ai
InstallView source
41Fair

Scored 5 months ago · breakdown

About Agentic RAG With MCP Server 1

Agentic RAG With MCP Server 1 is an MCP server published by iflow-mcp in the AI category: agentic RAG with MCP Server.

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

From source
git clone https://github.com/iflow-mcp/Agentic-RAG-with-MCP-Server-1

This 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 Agentic-RAG-MCPServer - AgenticRag

✨ 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 ClientSession from the mcp library
  • 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
  • openai Python package
  • mcp library
  • python-dotenv for 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

  1. Create a .env file (use .env.sample as a template)
  2. Set your OpenAI model in .env:
OPENAI_MODEL_NAME="your-model-name-here"
GEMINI_API_KEY="your-model-name-here"

🚀 How to Use

  1. Start the MCP server:
python server.py
  1. Run the MCP client:
python mcp-client.py

📜 License

This project is licensed under the MIT License.

Thanks for Reading 🙏

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Agentic RAG With MCP Server 1

How do I install Agentic RAG With MCP Server 1?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Agentic RAG With MCP Server 1 safe to use with an AI agent?

Its trust score is 41 out of 100 (fair). It passes 1 of the 2 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Agentic RAG With MCP Server 1 still maintained?

The last commit was 10 months ago. That's long enough that you should check whether the maintainer is responding to issues before depending on it.