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.

Skill Retriever is an MCP server based on a graph database, specifically designed for the retrieval and installation of Claude Code components. It automatically indexes component repositories on GitHub, returns the minimum correct set of components and their dependencies based on task descriptions through semantic search and graph traversal algorithms, and supports security scanning and automatic synchronization and updates.

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.

An MCP server that provides random algorithms and probabilistic decision-making capabilities. It extends sequential thinking through advanced mathematical models, helping AI assistants break out of local thinking patterns and make better decision plans.

PentestThinkingMCP is an automated penetration testing framework based on large language models and the MCP protocol. It can plan attack paths through Beam Search and MCTS algorithms, providing step reasoning, tool recommendation, and key path analysis for CTF, HTB, and real - world penetration testing.

QGIS MCP is a plugin that connects QGIS and Claude AI. It enables two-way communication through the Model Context Protocol, allowing AI to directly control QGIS for map project creation, layer loading, and processing algorithm execution.

Shebe is a fast full-text code search service based on the BM25 algorithm, designed specifically for Claude Code. It provides low-latency and high-efficiency code content retrieval, supporting multi-language code repository search and symbol reference lookup.

A trace analysis tool based on the large - text - viewer, supporting two modes: Trae Skill and MCP server. It provides functions such as text search, magic number identification, and search result optimization for reverse engineering and algorithm analysis.

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 intelligent e-commerce dialogue agent system based on reinforcement learning, integrating ontology reasoning, business toolchains, dialogue memory, and a Gradio interface. It realizes closed-loop learning from data to training and then to deployment through the Stable Baselines3 PPO algorithm, and can autonomously optimize the decision-making strategy of the shopping assistant.

RepoMap is a powerful code repository analysis and navigation tool that can be used as a command - line application or an MCP server. It intelligently analyzes the code structure and generates a prioritized code map through Tree - sitter code parsing and the PageRank algorithm.

This project is a Python implementation based on the Mozilla Readability algorithm, providing web page content extraction and conversion services through the MCP protocol, converting web page content into Markdown format suitable for LLM processing.

An MCP server based on Python that uses the Mozilla Readability algorithm to extract web page content and convert it into an optimized Markdown format.

An optimized Playwright MCP server that uses a client-server architecture to achieve browser automation. Through an innovative semantic snapshot algorithm, it significantly reduces the amount of page content transmission, while retaining key elements and reducing token consumption by 90%.

An all-in-one Docker image for the QuantConnect Lean algorithmic trading engine, supporting automatic GPU selection, a modern web interface, REST API, and MCP protocol integration

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

The Copus MCP server is a server based on the model context protocol that allows AI assistants to search for and retrieve human-curated content recommendations from the Copus platform. Copus is a discovery platform where real people recommend and explain the value of content, different from algorithm-driven search results. The server provides tools for searching curated content and obtaining detailed information, and is compatible with multiple AI platforms that support MCP.

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.

An MCP server for searching MCP protocol documents, providing intelligent search and document acquisition functions based on the BM25 algorithm.

Spotify Playlist MCP Server, supporting natural - language playlist creation and music recommendation with multiple similarity algorithms, including audio feature analysis and genre matching functions

PictMCP is an MCP server that provides reliable and algorithmically correct pairwise test generation for software developers using AI assistants to design test cases. It runs Microsoft's PICT algorithm locally using WebAssembly, separating the AI's thinking from combinatorial mathematics calculations to ensure the determinacy and correctness of test generation.

A test server project implementing the MCP algorithm, providing two communication methods: stdio and SSE

This project implements an MCP server for connecting to the TokenMetrics cryptocurrency data API, providing market data analysis, trading strategy backtesting, and visualization functions, and supporting the development of algorithmic trading systems.

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.

An MCP server based on Python that uses the Mozilla Readability algorithm to extract web page content and convert it into an optimized Markdown format, suitable for LLM processing.

An MCP server that provides Autodesk Alias API documentation search functionality for AI assistants, enabling fast retrieval through local indexing and the BM25 algorithm.

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.

QGIS MCP is an integrated tool that connects QGIS with Claude AI, enabling two-way interaction through the MCP protocol and supporting functions such as project creation, layer operation, and processing algorithm execution.