
mcp llama3 client
A client for the MCP Flight Search service using Ollama and Llama 3.2 to provide a user-friendly flight search interface with Model Context Protocol tools
Repository Info
About This Server
A client for the MCP Flight Search service using Ollama and Llama 3.2 to provide a user-friendly flight search interface with Model Context Protocol tools
Model Context Protocol (MCP) - This server can be integrated with AI applications to provide additional context and capabilities, enabling enhanced AI interactions and functionality.
Documentation
MCP Llama3 Flight Search Client
!MCP Flight Search Client Demo
A client for the MCP Flight Search service using Ollama and Llama 3.2 to provide a user-friendly flight search interface with Model Context Protocol tools.
Description
This client application provides a user-friendly interface to interact with the Model Context Protocol (MCP) flight search service. It allows users to search for flights between airports with specified dates.
About
A client for the MCP Flight Search service using Ollama and Llama 3.2 to provide a user-friendly flight search interface with Model Context Protocol tools
github.com/arjunprabhulal/mcp-llama3-client
Files
mcp_flight_client.py: Main client implementation for interacting with the MCP Flight Search serviceprompt_templates.py: Contains prompt templates for generating flight search queries
Installation
Install the required packages for this client:
pip install -r requirements.txt
Required packages:
- llama-index
- llama-index-llms-ollama
- llama-index-tools-mcp
- langchain-community
Installing Ollama
This client uses Ollama to run Llama 3.2 locally. To install Ollama:
- Download Ollama from the official website
- Install and start the Ollama application
- Pull the Llama 3.2 model:
ollama pull llama3.2
Prerequisites
You need to have the MCP Flight Search service running.
Installing the MCP Flight Search Package
# Install from PyPI
pip install mcp-flight-search
Starting the MCP Server
You can start the MCP server using one of the following methods:
!Starting the MCP Server
# Using the command-line entry point
mcp-flight-search --connection_type http
# Or using the Python module approach
python -m mcp_flight_search.server --connection_type http
Usage
python mcp_flight_client.py
Architecture
+------------------------------+ HTTP +------------------------------+
| | <------------> | |
| MCP Llama3 Flight Search | | MCP Flight Search Server |
| Client (This Repository) | | (Backend Service) |
| | | |
| - mcp_flight_client.py | | - search_flights_tool |
| - prompt_templates.py | | - server_status |
| | | |
| Uses: | | Uses: |
| - llama-index | | - Model Context Protocol |
| - llama-index-llms-ollama | | - SerpAPI for Google |
| (with Llama 3.2) | | Flights data |
| - llama-index-tools-mcp | | |
| - langchain-community | | |
+------------------------------+ +------------------------------+
| |
| |
v v
+------------------------------+ +------------------------------+
| | | |
| Ollama (Local LLM) | | Flight Search |
| Running Llama 3.2 | | APIs |
| | | |
+------------------------------+ +------------------------------+
|
|
v
+------------------------------+
| |
| User Interface |
| |
+------------------------------+
This architecture shows how the MCP Llama3 Flight Search Client connects to the MCP Flight Search Server over HTTP. The client uses various libraries to interact with the server, which in turn uses the Model Context Protocol (MCP) to provide flight search functionality through tools like search_flights_tool.
The client leverages Ollama to run Llama 3.2 locally, providing powerful language model capabilities while maintaining privacy and reducing dependency on cloud services.
Author
For more articles on AI/ML and Generative AI, follow me on Medium: https://medium.com/@arjun-prabhulal
License
This project is licensed under the MIT License
Quick Start
Clone the repository
git clone https://github.com/arjunprabhulal/mcp-llama3-clientInstall dependencies
cd mcp-llama3-client
npm installFollow the documentation
Check the repository's README.md file for specific installation and usage instructions.
Repository Details
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