"Finding MCP servers that support SSE or Streamable HTTP, excluding stdio transport" 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 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, 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 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.

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

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

Live Japan seasonal travel data from Japan Meteorological Corporation. 12 tools covering cherry blossom (sakura) forecasts, autumn leaves (koyo), fruit picking, flowers, festivals, and 3-day weather. 1,700+ GPS-tagged spots updated daily at 9AM JST. Works via npx or hosted HTTP endpoint — no auth required.

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.

The MCP server for Nanostores that scans your codebase with AST analysis to find stores, subscribers, and dependency chains, and can ingest live events to spot noisy, error-prone, or unused stores.

Single-binary Go MCP server that wraps whatsmeow to expose a personal WhatsApp account as 41 MCP tools (messaging, groups, polls, media, privacy).

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

An MCP server that turns AI assistants into competent Festo/CODESYS PLC engineers by grounding them in curated, manufacturer-accurate knowledge and forcing every artifact through a machine-checked validation pipeline for CODESYS import.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

Integrates HomeMatic smart home devices (via CCU3, RaspberryMatic, or debmatic) as MCP tools, enabling natural language query and control of rooms, devices, programs, and system variables.

Enables AI assistants to interact with a Magento 2 or Adobe Commerce MySQL database through 50+ read-only tools for orders, catalog, customers, CMS, configuration, indexers, and diagnostics, with support for local DDEV, Commerce Cloud, and remote/SSH connections.

An MCP server that enables AI assistants to perform web searches on Perplexity.ai using browser automation instead of an official API. It supports persistent authenticated sessions and returns search results along with cited sources directly to the client.

A smart AniList integration for the Model Context Protocol that provides AI assistants with tools for searching media, managing watchlists, and analyzing user anime or manga tastes. It goes beyond basic API calls by offering personalized recommendations, taste comparisons, and natural language profile summaries.