The MCP server for the 1000 Genomes Project dataset provides real - time natural language access to 3202 samples, 138 million variants, and approximately 442 billion genotypes in the Dnaerys variant storage, supporting screening and analysis based on coordinates, annotations, and genetic patterns.

FEGIS is a structured cognitive framework based on the Anthropic model context protocol, supporting the definition of cognitive tools through patterns and the persistent storage of cognitive products.

Grigori is a desktop application that helps developers manage and organize programming specifications, architectural patterns, and development preferences through the MCP protocol, enabling AI programming assistants to access personalized coding contexts.

Octocode MCP is an advanced AI code assistant that provides intelligent search and discovery functions across the GitHub and npm ecosystems. It helps developers quickly understand codebases, analyze project architectures, discover security patterns, and supports enterprise-level security and cross-platform use.

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 AI Code Toolkit provides MCP servers and tools to help AI programming agents maintain code consistency, follow conventions, and scale as the codebase expands, including scaffolding templates, architectural patterns, and validation rules

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.

A lightweight, configurable MCP server for development teams to obtain externally hosted coding specifications, security rules, and validation patterns.

An MCP server based on computer vision that automatically identifies the positions of image assets and extracts the layout structure by analyzing web page screenshots, supports the detection of multiple layout patterns such as radial and grid, and helps AI assistants accurately reconstruct web page layouts.

SourceSage is an MCP server that visualizes project directory structures into beautiful Markdown, supporting automatic file content documentation and flexible exclusion patterns.

The GLM-4.6 MCP Server is an enterprise-level architecture consulting protocol bridging service that connects Claude 4.5 Sonnet and GLM-4.6 through the model context protocol, providing system design, scalability patterns, and technical decision-making support. It supports functions such as code architecture analysis, system architecture design, and decision review.

The fabric-mcp-server is a server that implements the Model Context Protocol (MCP), integrating Fabric patterns as tools into Cline to enhance its AI-driven pattern execution capabilities.

Memory Bank MCP is a plugin that helps AI assistants maintain project context through structured Markdown files, providing a systematic way to track project goals, decisions, progress, and patterns.

The GitHub Code Review Assistant MCP Server provides intelligent tools to analyze PR code patterns, propose improvement suggestions, check compliance with team standards, and support a complete code review workflow.

ToolFront is an AI proxy database connection tool that securely connects coding assistants to team databases through the MCP protocol, enabling collaborative learning and sharing of query patterns.

This project contains the specifications and protocol patterns of the model context protocol, provides definitions in both TypeScript and JSON Schema formats, and includes an open - source contribution guide and MIT license.

The NestJS MCP module is an integration module designed for the NestJS framework to simplify the implementation of the Model Context Protocol (MCP) server. It supports multiple transport layers (including STDIO and HTTP/SSE) through decorators (such as @McpResource, @McpTool, @McpPrompt) and familiar NestJS patterns, enabling developers to quickly build MCP - compatible services.

The Lunch Flow MCP Server allows users to query bank account data connected to AI assistants such as Claude through natural language. It supports access to the balances, transaction records, and spending patterns of over 20,000 banks worldwide and needs to be used with a Lunch Flow account.

A code security firewall MCP service based on structural similarity. It intercepts malicious code patterns before code execution by parsing the code structure and comparing it with the blacklist of dangerous patterns.

Nano Banana is a professional MCP extension for generating, editing, and restoring images through text descriptions. It supports various image processing functions, such as generating icons, patterns, stories, and diagrams.

An MCP server based on Faker.js, providing the function of generating mock test data. It supports multiple data types, custom patterns, and structured datasets, and is suitable for database filling, API testing, and development environments.

The Atuin integration project provides two - way bash history synchronization for Claude Code. It records commands executed by Claude to the atuin history through a write hook and allows Claude to query the user's historical command patterns through the MCP server.

This is an MCP server for Microsoft Dynamics 365 Finance & Operations development. It accesses over 50,000 F&O standard components through semantic search, enabling AI assistants to find relevant implementation patterns and read local source code during development.

Learning notes for Java software development, covering technical topics such as core Java, Web development, and design patterns, including detailed technical discussions, code examples, and best practices.

An AI - based educational platform for Quranic etymology exploration, offering etymology analysis, frequency patterns, and multilingual research functions, including complete project context, database schema, and automated workflows.

Brainrot MCP is a model context protocol server that solves the problem of context loss in AI programming conversations. By storing project decisions, to - do lists, and architectural patterns, it enables persistent memory and intelligent retrieval across conversations.

This is a MIDI controller project that controls the Teenage Engineering EP-133 K.O. II sampler through the MCP protocol. It supports playing notes, rhythm patterns, and drum patterns using text commands, and can be integrated with Claude to achieve natural language control.

CodeSentinel is a code quality analysis server based on the Model Context Protocol (MCP), specifically designed to detect 93 hidden problem patterns in AI-generated code, including security vulnerabilities, deceptive error handling, placeholder code, etc. It uses pattern matching rather than AST analysis to find code that is syntactically correct but semantically problematic.

This project is a Python development environment template based on Devcontainer. It comes pre - configured with Python 3.11, the pytest testing framework, the flake8 code inspection tool, and the black code formatting tool. It provides a consistent and isolated development environment and includes sample code for basic syntax and design patterns.

A file system MCP server implemented in Go language, providing a variety of file operation tools, supporting JSON data return and gitignore-style exclusion patterns.

A four - stage Reading Companion MCP server that helps users read systematically and learn deeply by establishing a reading profile through interviews, analyzing patterns, recommending book lists, and guiding reflections.

The Kubit MCP Server is a tool that connects the data warehouse analysis platform with an AI assistant, allowing users to query, explore data patterns, generate reports, export data, and search for existing analysis content through natural language without writing complex query statements.

MCPLab is a collection project of server-client examples, code snippets, design patterns, and tutorials focused on the Model Context Protocol (MCP), aiming to help developers quickly build MCP-driven applications.

An MCP server that transforms Claude into a structured interviewer. Through a shared evolution system, each conversation makes the system smarter. The system automatically optimizes interview checkpoints and paths based on Bayesian scoring and community usage patterns, achieving collective knowledge evolution.

Fabric Atelier is a high-performance MCP server built on Rust and Apache Arrow, exposing over 200 Fabric AI patterns as executable tools to AI assistants, supporting semantic search and quick pattern discovery.