Discover our curated collection of MCP servers for learning & documentation. Browse 1661servers and find the perfect MCPs for your needs.
Provides intelligent recommendations for other Model Context Protocol (MCP) servers tailored to specific development requirements.
Enables AI assistants to understand and generate GPAC command examples by providing intelligent access to the GPAC multimedia framework test suite.
Enables AI agents to understand and interact with the Optics Design System's tokens, components, and documentation.
Programmatically retrieve cryptographic research papers from the IACR Cryptology ePrint Archive.
Provides a Model Context Protocol server for Zettelkasten note management, enabling comprehensive search, creation, and link analysis of notes.
Provides a practical example for developing Gemini CLI extensions.
Provides an educational example of an MCP server to expose tools, resources, and prompts to AI clients using the FastMCP library.
Provides slides and materials for a workshop on deploying applications to Kubernetes.
Guides users through creating Non-Disclosure Agreements (NDAs) using eSignatures.
Visualize source code, files, and folder structures as interactive, AI-assisted graphs to understand project hierarchies and code relationships.
Provides seamless access to the GTFOBins database directly within Claude Desktop for querying exploitation techniques and privilege escalation methods.
Guide users through transforming ideas into websites and apps using AI tools, covering prompt engineering, UI design, and development best practices.
Automates the generation of typed React hooks and comprehensive documentation for Next.js projects, enhancing developer workflow with AI, CI/CD, and type safety.
Provides Metal Framework documentation search and code generation capabilities via the MCP protocol.
Demonstrates creating MCP clients and servers in Python and TypeScript, integrating with local LLMs.
Provides AI agents with professional development guidelines, coding standards, and best practices for writing production-quality code.
Provides AI assistants with contextual, version-specific documentation for Python project dependencies, eliminating manual package lookup and enhancing coding assistance.
Offers a Go library for implementing post-quantum cryptographic algorithms such as ML-DSA for digital signatures and ML-KEM for key encapsulation.
Find battle-tested solutions to coding problems from across the programming community, bypassing generic documentation and AI hallucinations.
Integrates with Zotero, enabling AI applications to access and manipulate Zotero libraries.
Scroll for more results...