A Model Context Protocol server that provides EigenLayer documentation to AI assistants like Claude, enabling natural language interaction with EigenLayer concepts and functionality.
Helps migrate projects from AI SDK 4.x to 5.0 by generating a migration checklist and searching the official migration guide for code and data changes.
Auto-discovers llms.txt documentation from project dependencies and exposes it to AI coding agents via MCP, enabling agents to read first-party docs without scraping or guessing.
The Metaplex MCP Server facilitates access to Metaplex documentation and repository details, enabling users to search and interact with various Metaplex resources through the MCP protocol.
Provides a comprehensive robotics information hub with details on frameworks like ROS and Gazebo, robot types, and curated learning resources. It enables AI assistants to access offline robotics documentation and development roadmaps without external API dependencies.
Two MCP endpoints for building cognitive AI agents. /blueprint/mcp serves a 9-chapter architecture blueprint (4 tools). /devops/mcp serves a 7-chapter coding agent playbook (3 tools). Each product has its own Gumroad license key. Free chapters available without auth.
A read-only reference server for 303 curated generative art algorithms implemented in Python (py5), spanning physics, fractals, cellular automata, shaders, and more. Agents can search by keyword, visual mood (ethereal, chaotic, crystalline…), or multi-layer artistic intent to discover algorithms, read structured summaries, and fetch bounded source snippets.
Deterministic navigation maps over code AND markdown for AI agents: one MCP server, two lenses (tree-sitter TS/JS/Python + markdown). Map a whole project, read one function or one doc-section, ~99% less context. Merges codelens + docslens.
An MCP server that provides AI coding assistants with access to official ARM CMSIS SVD hardware register definitions for microcontrollers. It enables precise querying of register names, bit positions, and addresses to prevent hallucinations during embedded systems development.
Enables intelligent navigation and extraction of documentation from websites, allowing Amazon Q to automatically discover relevant pages, extract clean content, and retrieve code examples from web documentation.
A TypeScript-based server that visualizes project directory structures in Markdown format, automatically documenting file contents with syntax highlighting and supporting customizable exclusion patterns.
Bridges AI coding assistants with the OpenTelemetry ecosystem, providing real-time access to repositories, documentation, examples, semantic conventions, and instrumentation scoring for high-quality observability.