"Simple MCP example using HTTP transport" matching MCP servers:

Turns any API into a curated MCP server from a single config file, enabling interaction with APIs through MCP clients like Claude Desktop.

A Model Context Protocol (MCP) server for accessing Productive.io API endpoints (projects, tasks, comments, todos), tailored for read-only operations, providing streamlined access to essential data while minimizing token consumption

MCP server for Wiki.js that exposes 29 tools for managing pages, comments, tags, assets, users, navigation, and more via HTTP/SSE with built-in mutation safety.

MCP server that helps AI assistants generate accurate code and guidance for Dynamsoft SDKs.

A simple MCP server for utilizing prompts defined in YAML files.

Read-only MCP server for self-hosted Confluence that lets AI agents search pages, fetch content, and navigate page trees via the REST API.

Enables AI assistants to explore, search, and read codebase repositories and API specifications efficiently, with support for file searching, content search via ripgrep, and reading API specs.

Educational example of an MCP server built with FastMCP, demonstrating how to expose tools, resources, and prompts for AI clients.

Enables hybrid search (BM25 + semantic with RRF) over documentation, with Thai language support. It exposes MCP tools for adding documents and searching via Qdrant and Ollama/OpenAI, using a stateless Streamable HTTP transport.

A dependency-free MCP server providing tools for tailing logs, checking endpoint health, and searching/updating a runbook of past fixes.

Provides calculator tools for mathematical operations, access to TypeScript SDK documentation, and meeting summary prompt templates through both stdio and SSE transports.

Extracts and stores documentation content from Microsoft Learn and GitHub URLs into PocketBase with full-text search, metadata preservation, and automatic collection management for easy retrieval and organization.

Provides calculator tools for mathematical operations, document resources for accessing TypeScript SDK documentation, and prompt templates for generating structured meeting summaries. Built with FastMCP to demonstrate comprehensive MCP capabilities including tools, resources, and prompts in a single implementation.

Makes local markdown documentation files automatically available to AI assistants through MCP, enabling them to search and read organized documentation folders without manual file registration.

Provides tools to summarize README files from local paths or public Git repositories into structured JSON summaries. It enables users to quickly extract key facts and project overviews from documentation through automated tool calls.

Enables AI assistants to access and search MkDocs documentation through tools for full-text search, page navigation, and code block extraction. It serves documentation pages as readable resources and provides structural outlines to help LLMs navigate documentation content.

Enables LLM clients to discover, load, and execute markdown skills with bundled scripts over HTTP, featuring progressive disclosure and sandboxed script execution with timeout and stall detection.

Enables AI models to access GitHub repository information and search local documentation files. Provides three basic tools: fetching repository details, retrieving file contents from GitHub, and searching through local markdown documentation.

Exposes a folder of Markdown runbooks to an AI assistant via three tools (list_notes, search_notes, read_note) over MCP's streamable-http transport.

Enables AI models to fetch GitHub repository information, read file contents, and search local documentation.