Learning & Documentation MCP Servers

Discover our curated collection of MCP servers for learning & documentation. Browse 431 servers and find the perfect MCPs for your needs.

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Canvas LMS

Enables student access to Canvas LMS resources through an MCP server.

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Party Time

Responds with 'It's Party Time' when asked about the current time via the Machine Conversation Protocol.

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Introduction To

Illustrates basic calculator operations using SSE and stdio transports with a minimal Model Context Protocol (MCP) server and client example.

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Learn MCP By Building

Implement the Model Context Protocol (MCP) by building AI tools with a modular framework for creating MCP-compatible servers and clients.

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Rememberizer

Enables Large Language Models to search, retrieve, and manage documents and integrations through Rememberizer's API.

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Github

Documents the setup and configuration process for a GitHub Model Context Protocol (MCP) server.

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Jayanth-MKV

Explore and learn about Model Context Protocol (MCP) server implementations through a collection of experimental servers.

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Instruction Server

Provides AI assistants access to a library of structured markdown instructions via the Model Context Protocol (MCP).

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Go

Enables AI assistants to access Go documentation and package listings via the Model Context Protocol.

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473 Project

Integrates with the NASA API to provide users with space-related information and imagery.

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Server Learning

Provides a learning environment for understanding and implementing Model Context Protocol (MCP) servers.

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CrazyrabbitLTC Expert

Generates intelligent queries and documentation assistance for APIs using Claude AI.

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Arxiv Search

Enables LLMs to search and retrieve academic papers from arXiv, providing cleaned titles, abstracts, and content.

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Zotero

Integrates with Zotero, enabling AI applications to access and manipulate Zotero libraries.

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Seta

Powers an Model Context Protocol (MCP) server with documentation sourced from a local file system.

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Model Context Provider

Provides a server for managing model context during development and learning.

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Docs Search

Enables LLMs to dynamically search and retrieve up-to-date documentation from popular AI libraries.

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Etabs Documentation Assistant

Enables semantic search of user-provided ETABS documentation using local embeddings and a Model Context Protocol (MCP) server.

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Ladeira Learning

Provides resources for learning how to build servers for connection to Large Language Models (LLMs) using Langchain.

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Perplexity

Enhances Claude's web search capabilities using Perplexity's API, offering intelligent model selection, domain filtering, and recency control.

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