Learning & Documentation MCP 服务器
发现我们为 learning & documentation 精心策划的 MCP 服务器集合。浏览 1045 个服务器,找到满足您需求的完美 MCP。
LeetCode
Enables advanced automation and intelligent interaction with LeetCode's problems, contests, solutions, and user data.
Logseq Tools
Enables AI assistants to interact with and extract information from a Logseq knowledge graph.
Deep Research
Conducts iterative, deep research using search engines, web scraping, and Gemini LLMs to create an AI Research Agent.
Scrapling Fetch
Retrieves text and HTML content from bot-protected websites for AI assistant consumption.
React Analyzer
Analyzes React code and generates documentation locally using the Model Context Protocol.
Discovery
Discovers and documents MCP Server capabilities using a command-line interface.
Svelte5
Provides curated knowledge, code examples, and intelligent assistance for Svelte 5 frontend development.
Canvas
Manages courses, assignments, enrollments, and grades within Canvas using the Canvas API.
DeepSRT
Generates summaries of YouTube videos via the Model Context Protocol.
Linkup
Enhances Claude AI with real-time web search and premium content access.
OpenAPI Schema Explorer
Provides token-efficient access to OpenAPI/Swagger specifications via MCP Resources for client-side exploration.
Memory Bank
Manages memory banks, enabling AI assistants to store and retrieve information across sessions for maintaining context.
Rust Docs
Retrieves Rust crate documentation from docs.rs to provide LLMs with context for working with Rust code.
Docs Service
Manages markdown documentation with frontmatter, optimized for AI assistant integration.
Rtfmbro
Provides AI coding agents with always-up-to-date, version-specific package documentation as context.
Ragdocs
Augments AI responses with relevant documentation context through vector search.
Python Dependency Manager Companion
Provides a local server that unifies and makes instantly searchable the latest documentation for various Python dependency managers directly within your agentic IDE.
OpenAPI Schema
Enables Large Language Models to explore and understand OpenAPI specifications through specialized tools.
Context Optimizer
Optimizes context for AI coding assistants by enabling them to extract targeted information from files and command outputs, rather than processing large data in its entirety.
MATLAB
Enables AI users to execute MATLAB code, generate scripts from natural language, and access documentation directly within conversations.
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