MCP_Server

# Model Context Provider (MCP) Server ## Overview The **Model Context Provider (MCP) Server** is a lightweight and efficient system designed to manage contextual data for AI models. It helps AI applications retrieve relevant context based on user queries, improving the overall intelligence and responsiveness of AI-driven systems. ## Features - **Context Management**: Add, update, and retrieve structured context data. - **Query-Based Context Matching**: Identify relevant contexts using a keyword-based search algorithm. - **JSON-Based Storage**: Handles structured AI context data. - **File-Based Context Loading**: Load context dynamically from external JSON files. - **Debugging Support**: Provides detailed debug logs for query processing. ## Installation To install and run the MCP Server, follow these steps: ```sh # Clone the repository git clone https://github.com/your-repo/mcp-server.git cd mcp-server # Install dependencies pip install -r requirements.txt ``` ## Usage ### 1. Initialize MCP Server ```python from mcp_server import ModelContextProvider mcp = ModelContextProvider() ``` ### 2. Add Context ```python mcp.add_context( "company_info", { "name": "TechCorp", "founded": 2010, "industry": "Artificial Intelligence", "products": ["AI Assistant", "Smart Analytics", "Prediction Engine"], "mission": "To make AI accessible to everyone" } ) ``` ### 3. Query Context ```python query = "What are the features of the AI Assistant product?" relevant_context = mcp.query_context(query) print(relevant_context) ``` ### 4. Provide Context to AI Model ```python model_context = mcp.provide_model_context(query) print(model_context) ``` ## API Methods | Method | Description | |--------|-------------| | `add_context(context_id, content, metadata)` | Adds or updates a context. | | `get_context(context_id)` | Retrieves context by ID. | | `query_context(query, relevance_threshold)` | Finds relevant contexts based on a query. | | `provide_model_context(query, max_contexts)` | Returns structured model-ready context. | ## Contributing We welcome contributions! If you want to improve MCP Server, feel free to fork the repo and submit a pull request.