This repository provides a comprehensive Model Context Protocol (MCP) server implementation, targeting developers and researchers building AI-powered applications that require structured interaction with language models and data sources. It offers a unified server for tools, resources, prompts, and advanced sampling, integrating HackerNews and GitHub APIs for AI-driven analysis.

How It Works

The server implements the MCP 2025-03-26 specification, acting as a central hub for AI interactions. It leverages an async/await framework for performance, supporting Server-Sent Events (SSE) for transport. Key features include a rich set of MCP tools (e.g., search_hackernews, create_sampling_request), 15 distinct MCP resources (e.g., hackernews://top/10, github://trending/python/daily), and 14 prompt templates for various AI tasks. Enhanced sampling allows for model preferences (intelligence, cost, speed) and context-aware requests.

Quick Start & Requirements

• Installation: pip install -r requirements.txt
• Running the Server: cd src && python mcp_server.py
• Prerequisites: Python environment. No specific hardware or GPU requirements are mentioned for core functionality.
• Documentation: Technical Architecture, CLI Usage Guide

Highlighted Details

• Full MCP 2025-03-26 specification compliance for tools, resources, prompts, and enhanced sampling.
• Production-ready core features with 9/9 tools, 15/15 resources, and 14/14 prompts passing tests.
• Enhanced sampling supports model preferences (intelligence, cost, speed) and model hints (e.g., "claude-3-sonnet").
• Integrates HackerNews and GitHub APIs for data retrieval and AI-powered analysis.

Maintenance & Community

No specific community channels (Discord/Slack) or roadmap links are provided in the README. The project appears to be a solo effort by "hemanth".

Licensing & Compatibility

The project is licensed under the MIT License, permitting commercial use and integration with closed-source projects.

Limitations & Caveats

The "MCP Roots" functionality has known framework concurrency limitations, and enhanced sampling tests indicate server concurrency constraints under load. While core MCP features are production-ready, these specific areas are marked with warnings and have incomplete test suite results.