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MCP server · AI

Agentic RAG With MCP Server

by · github.com/ashishpatel26/Agentic-RAG-with-MCP-Server

Agentic RAG with MCP Server

Unclaimed last commit a year ago ai
InstallView source
46Fair

Scored 3 months ago · breakdown

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. It has been installed 0 times through Conduid.

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 (0) before depending on it in production.

Install

Install
npx agentic-rag-with-mcp-server

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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  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

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 mirrored from the source repository 3 months ago. The original is authoritative.

Questions

About Agentic RAG With MCP Server

How do I install Agentic RAG With MCP Server?

Run npx agentic-rag-with-mcp-server, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

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

Its trust score is 46 out of 100 (fair). It passes 0 of 1 static security checks; 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 still maintained?

The last commit was a year ago, with 0 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.