"Learning to Read and Use GitHub Project Documentation" matching MCP servers:

A custom MCP server providing tools for date/time, calculations, mock weather, and note management, enabling AI agents to perform these tasks via natural language.

An MCP server that reads public GitHub Projects v2 boards (including item-level data like status and custom fields) without authentication, using official APIs and fallback methods for user-owned projects.

An MCP server that enforces a pedagogical workflow to teach topics step by step, using research, decomposition, and spaced retrieval practice.

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

Provides full-text search and retrieval tools for Apache Spark documentation using SQLite FTS5 with BM25 ranking. It enables AI assistants to efficiently search, filter by section, and read specific Spark documentation pages.

A server that enables Claude to search and access documentation from popular libraries like LangChain, LlamaIndex, and OpenAI directly within conversations.

Enables educational and learning tasks including flashcard generation with Anki integration, Zotero library management, Obsidian vault interaction, and mathematical expression verification with LaTeX support.

A Model Context Protocol server that enables AI agents to access, search, and understand structured package documentation and source code from Git repositories. It automatically generates specialized tools to browse module overviews, components, and detailed documentation for technical libraries.

A comprehensive learning project demonstrating MCP server implementation with tools for calculator operations, file management, and system information retrieval, including Google ADK integration patterns and best practices.

Enables Claude to see and control a real Android phone via MCP, reading the accessibility tree to tap, type, navigate, launch apps, and diagnose connectivity over ADB or cellular.

Enables autonomous learning from interactions through pattern recognition and machine learning techniques. Continuously improves performance by analyzing tool usage, providing predictive suggestions, and sharing knowledge across MCP servers.

Provides a universal read path for agents to extract facts, metadata, and provenance from local files and guarded remote URLs without using generative LLMs.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

Enables AI agents to autonomously operate web browsers through the Model Context Protocol, including navigating pages, clicking, typing, filling forms, and extracting structured data.

Allow to manage Issues and Project on Github

Enables Claude to read-only browse, search, and fetch emails from a Proton Mail inbox through Proton Bridge IMAP, with no capabilities to send, move, flag, or delete.

A learning MCP server that transforms technical topics into four structured parts: definition, analogy, example, and hands-on try-it exercises, enabling beginner-friendly study directly from any MCP client.

Provides 39 tools to manage GitHub repositories, branches, issues, PRs, workflows, and more via the GitHub CLI, enabling natural language interaction with GitHub.

An artifact store that lets coding agents and small teams publish, version, and review web artifacts through an MCP server or CLI, with stable URLs, access gates, and comments.

Provides stateful prompt optimization using research-backed techniques like APE and OPRO, learning from historical performance data via a vector database. It enables users to automatically refine prompts, retrieve high-performing examples, and track performance analytics through iterative feedback.