MCP Server
by Chris-June / IntelliSync Solutions
MCP (Model Context Protocol) Server is an AI-powered server providing intelligent, context-aware conversational capabilities. It leverages multiple LLM providers and web browsing capabilities to deliver nuanced responses.
Last updated: March 23, 2025
What is MCP Server?
The MCP Server is a sophisticated AI-powered server designed to provide intelligent, context-aware conversational capabilities. It acts as a standalone server that can be integrated with any frontend through its RESTful API.
How to use MCP Server?
To use the MCP Server, you need to clone the repository, set up the environment, configure the necessary API keys, and run the server. Detailed instructions are provided in the README, including steps for installing dependencies and accessing the API documentation.
Key features of MCP Server
Role-based AI advisor system with customizable instructions and tones
Semantic memory management with vector similarity search
Real-time streaming responses for improved user experience
Integrated web browsing capabilities for AI-assisted research
Multiple LLM provider support (OpenAI, Anthropic, Google Gemini)
Use cases of MCP Server
Small Business Executive Advisory
Customer Service Automation
AI-assisted Research
Personalized Learning Platforms
FAQ from MCP Server
What is the purpose of the MCP Server?
What is the purpose of the MCP Server?
The MCP Server provides intelligent, context-aware conversational capabilities by leveraging multiple LLM providers and web browsing.
What LLM providers are supported?
What LLM providers are supported?
The MCP Server supports OpenAI, Anthropic, and Google Gemini.
How do I configure the server?
How do I configure the server?
You need to create a .env file based on .env.example and configure the necessary API keys and model settings.
Is a frontend included in this repository?
Is a frontend included in this repository?
No, this repository contains only the MCP server implementation. Frontend examples are provided in the documentation for illustrative purposes.
How do I access the API documentation?
How do I access the API documentation?
After running the server, you can access the API documentation at http://localhost:8000/docs.