MCP Reasoner is a tool designed for Claude Desktop to enhance reasoning capabilities. It provides two algorithms, Beam Search and Monte Carlo Tree Search, and adds an experimental strategy simulation layer to optimize the solution of complex problems.

MCP Reasoner is an inference enhancement tool designed for Claude Desktop, providing two search strategies, Beam Search and MCTS, and improving the ability to solve complex problems through experimental algorithms.

A Model Context Protocol (MCP) server for encryption/decryption/algorithms/hashing, supporting AES, DES, multiple hashing algorithms, and encoding/decoding functions

A Model Context Protocol (MCP) server implemented for NebulaGraph, providing seamless access to NebulaGraph, supporting graph exploration, querying, and shortcut algorithms, and being easily integrated with LLM tool systems.

A memory system that enhances AI programming capabilities through multi-type database integration, including vector databases, SQLite, and knowledge graphs, for storing and retrieving code patterns, algorithms, and relationships between programming concepts.

The Unsloth MCP Server is a server for efficiently fine-tuning large language models. Through optimized algorithms and 4-bit quantization technology, it achieves a 2-fold increase in training speed and an 80% reduction in video memory usage, supporting multiple mainstream models.

The Context Engineering MCP Platform is an AI context management and optimization platform that designs, manages, and optimizes the input information of AI models through a systematic approach, realizing the engineering of prompt engineering. The platform provides functions such as intelligent analysis engines, optimization algorithms, and template management, significantly improving AI response quality, reducing API costs, and supporting multimodal content processing.

An MCP service that automatically optimizes AI prompts based on evolutionary algorithms, iteratively improving prompt performance through genetic algorithms

The OpenFacet MCP Server is an implementation based on the Model Context Protocol (MCP), specifically designed for the OpenFacet diamond pricing API. It provides transparent real-time diamond pricing data, including interpolation algorithms and in-depth market analysis. This project is written in pure JavaScript, has no external dependencies, and supports both Node.js and Cloudflare Worker runtime environments.

The DocuMind MCP Server is a next-generation document quality analysis server based on neural networks. It provides functions such as README evaluation, SVG header image scanning, and multi-language support through advanced algorithms, and offers AI-driven document improvement suggestions for developers.

An implementation of the Model Context Protocol server for NebulaGraph, providing seamless access to NebulaGraph and supporting graph exploration, querying, and quick algorithms.

The NSAF MCP Server is a server-side implementation of the Model Context Protocol (MCP) used to connect AI assistants with the Neural-Symbolic Autonomous Framework (NSAF), providing evolutionary algorithms and architecture comparison functions.

DocuMind MCP Server is a document quality analysis server based on neural networks. It comprehensively evaluates README files through advanced algorithms, provides improvement suggestions, and supports multi-language document verification and SVG header image analysis.

The NSAF MCP Server is a server-side service for the neural-symbolic autonomous framework based on the Model Context Protocol, allowing AI assistants to interact with the NSAF framework through the MCP protocol and providing functions such as running evolutionary algorithms and comparing intelligent agent architectures.

An MCP server built on FastMCP, providing a secure OTP (one-time password) generation function, supporting the TOTP and HOTP algorithms, and offering multiple transmission options for integration with AI assistants and applications.

A learning path generation server based on FastAPI that can create structured learning plans for any topic, integrate online resources, and optimize content organization and performance through intelligent algorithms.