What does the `get_city_weather` tool return?
It returns dummy weather information including temperature, description, and humidity, along with `structuredContent` matching a defined `outputSchema` for reliable client parsing.
@EnigmaticHarvest
Basic information
A dummy MCP server to test the mcp-chat-cli at
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
My MCP Weather Server is an example MCP (Model Context Protocol) server built with the @modelcontextprotocol/sdk for TypeScript. It exposes a single tool that returns dummy weather information for a few predefined cities, intended for use as a backend by MCP-compliant clients such as LLM‑powered agents.
Clone or create the project, install dependencies with npm install, then run npm run build (or use the development command with ts-node and nodemon). The server uses Streamable HTTP Transport; clients call the get_city_weather tool by providing a city string and an optional unit parameter.
get_city_weather tool with structured outputIt returns dummy weather information including temperature, description, and humidity, along with `structuredContent` matching a defined `outputSchema` for reliable client parsing.
Node.js v18 or higher and npm (or yarn/pnpm). The server uses the `@modelcontextprotocol/sdk` and runs via `ts-node` in development mode.
No. All weather data is dummy/in‑memory for a few predefined cities (e.g., paris, london, tokyo). It is an example server, not a production service.
It uses `StreamableHTTPServerTransport`, the recommended MCP transport for HTTP‑based communication.
The server demonstrates basic in‑memory session handling, but no authentication mechanism is implemented.

Generate images, video, audio and short films with 140+ AI models from any MCP client. PixelDojo picks the right model (Flux, Seedream, Seedance, Veo, Kling, WAN, Nano Banana, GPT Image), renders it and returns download

EveryGen AI MCP Server lets AI assistants create videos, images, voiceovers, music and complete multi-shot films. Connect your EveryGen AI account, describe what you want, review the credit quote and approve the creation

Creates and manages quizzes, polls, surveys, personality tests, forms, predictors, minigames and leaderboards on Riddle.com – with branching logic, custom design, live stats and embed code.
Give your AI agent a real design engine. Create, edit and export real, editable designs from Claude Code, Codex, Cursor and more.

Transcribe YouTube videos, podcasts, meetings and media links into speaker-labelled, timestamped transcripts, then search who said what, ask questions answered with timestamped citations, pull chapters and paste-ready ti
Comments