"Python Object-Oriented Programming Resources" matching MCP servers:

A production-grade, extensible Python template for building Model Context Protocol servers with support for Streamable HTTP and stdio transports. It provides a structured framework for implementing tools, resources, and prompts with built-in authentication, observability, and background task management.

Provides complete access to Model Context Protocol documentation through an MCP server, allowing LLMs to query specific sections like 'Tools', 'Resources', and 'Authorization' to retrieve comprehensive protocol specifications.

MCP server providing token-efficient access to OpenAPI/Swagger specs via MCP Resources for client-side exploration.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.

Provides local, offline searchable access to Roku and BrightScript development documentation via MCP tools and resources, including full-text search, sectioned reading of large docs, and background syncing from the upstream repo.

Provides read-only access to the ProPaths verified protein interactome, letting AI agents search proteins, retrieve mechanistic interaction details, and explore pathway ontology through MCP tools, resources, and prompts.

A task-board MCP server that provides tools to search, create, and update tasks, resources for reading the board, and prompts for standup and triage workflows.

Provides a Model Context Protocol server with tools for knowledge base search, retrieval, and addition, plus system time, resources, and prompts. Supports stdio and Streamable HTTP transports for local and shared deployments.

Provides AI coding assistants with access to AccelByte Gaming Services (AGS) Extend SDK functions and models through searchable symbols and detailed documentation. Helps generate SDK code by exposing context about available functions, models, and templates for creating Extend app projects across multiple languages (Go, C#, Java, Python).

Provides comprehensive documentation for MAX Platform, including Bot API endpoints, guides, Bridge API, and UI components, via MCP tools and resources for AI coding agents.

Enables Claude and ChatGPT to help users pick UC Irvine classes by searching live course sections, comparing grade distributions by instructor, checking prerequisites and AP credit, and detecting schedule conflicts, all through tools, guided prompts, and reference resources.

Exposes Cursor-style skill packs (SKILL.md trees) via MCP resources, tools, and prompts, enabling any MCP client to list, get, search skills, and retrieve skill context.

A production-grade TypeScript starter for building Model Context Protocol servers, supporting stdio and Streamable HTTP transports with modular tools, resources, and prompts.

A production-grade MCP server that provides real-time weather data and demonstrates the complete MCP protocol surface including tools, resources, prompts, and structured output.

An MCP server that demonstrates the Model Context Protocol using a mock SQLite database of an online store, offering tools for product search, sales analysis, and reviews, along with resources and prompts for learning MCP integration.

A Know Your Business workbench that searches French company registry data, manages review dossiers, and exposes tools, resources, prompts, completions, elicitation, and sampling to any MCP client.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

A Python MCP server for web research that enables fetching web pages, searching, batch-fetching, extracting links, and summarizing content via client-side sampling, with optional local file access.

Enables sending web push notifications and managing Pushpad resources (notifications, subscriptions, projects, and senders) through natural language, using the Pushpad API.