"Golang HTTP streaming with MCP examples" matching MCP servers:

Enables AI agents to send HTTP requests to any endpoint with full control over methods, headers, query parameters, and request bodies.

Enables AI assistants to read, search, and traverse your reMarkable tablet's library, including handwritten notes via OCR.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

MCP server for the ReactUse library. Exposes 110+ React Hook signatures, examples, and API metadata so AI coding assistants can discover and use any hook from @reactuses/core directly.

mistral-mcp is a TypeScript MCP server (spec 2025-11-25) that exposes the full Mistral AI API surface: 22 tools: chat, OCR, audio (Voxtral), vision, agents, embeddings, moderation, classification, files, batch, sampling, FIM (Codestral), streaming 2 resources: mistral://models, mistral://voices 6 curated prompts (French + English) with MCP argument completion Dual transport: stdio (default) + Str

Exposes WAI-ARIA Authoring Practices Guide (APG) patterns, providing narratives, keyboard guidance, and official source code examples for accessible widgets. It includes tools for listing patterns, retrieving specific specs, and performing semantic searches via Ollama.

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.

MCP server that injects verified FTC documentation and code examples into AI assistants, enabling teams to write correct, competition-ready Java robot code through natural language.

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

Trade, analyze, and automate Polymarket prediction markets via AI. 34 tools for direct trading, smart money flow, copy trading, backtest, and portfolio management.

MCP server to access and search adonis-mcp documentation files from GitHub, with tools for listing, searching, and extracting code examples.

MCP server for retrieving FAQ and glossary from the hotline.finance insurance service, supporting both stdio and HTTP modes for integration with clients like Cursor, Claude Desktop, and ChatGPT.

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.

A local MCP server that connects to SAP ABAP systems via ADT HTTP API, enabling AI assistants to search, read, and manage ABAP objects securely without SAP GUI.

A task management MCP server for AI-driven development, enabling creation, tracking, and organization of tasks with subtasks, priorities, and dependencies via natural language commands.

An MCP server providing full integration with the Lunch Money API to manage financial data including transactions, budgets, assets, and categories. It enables AI assistants to perform CRUD operations on financial records through a standardized HTTP interface.

A minimal TypeScript starter template for building Model Context Protocol (MCP) servers with auto-loading architecture for tools, resources, and prompts. Includes code generators, dual transport support (stdio/HTTP), and production-ready structure.

A flexible proxy server that aggregates multiple backend MCP servers into a single interface using STDIO or SSE transports. It supports dynamic server management via an HTTP API and utilizes namespacing to prevent tool conflicts across connected services.

Integrates front-end development servers with AI tools, enabling browser automation, console log capture, screenshot management, and HMR event monitoring.