aidaily

# MCP Demo [](https://smithery.ai/server/@PawNzZi/aidaily) This is a basic MCP server implementation, that exposes data and actions for a connected large language model to use. ## Example usage for ChatGPT Give the following instructions to ChatGPT after starting the server ``` - You are connected to a remote tool MCP Demo. - I will describe the usage of functions it contains, the schemas for each function's arguments, and the expected return format. 1. resources/list: Get a list of available resources. Takes no arguments, returns an array of resources with URIs and MIME types 2. tools/list: Get a list of available tools. Takes no arguments, returns an array of tool names 3. tools/call : Use a tool. Required parameters: 'name': The string name of the tool you want to use, 'params': A dictionary representing the tool's arguments 4. prompts/get: Retrieve a prompt. Required parameter: 'name': The string name of the prompt you want to retrieve, returns a string of the prompt text Thank you, and welcome to MCP Demo ``` ## Get Started ### Installing via Smithery To install MCP Demo for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@PawNzZi/aidaily): ```bash npx -y @smithery/cli install @PawNzZi/aidaily --client claude ``` ### Resources The MCP Demo includes example resources that can be queried: ``` resources = [ {"name": "Hello World", "uri": "text://hello-world", "mimeType": "text/plain"}, {"name": "Introduction to Large Language Models", "uri": "text://introduction-to-llms", "mimeType": "text/plain"} ] ``` A line from an `Introduction to Large Language Models` ``` 1. History: Large Language Models (LLMs) trace their roots to early research in artificial neural networks ``` The returned JSON-encoded response of the `tools/list` call should look something like: ``` {"jsonrpc":"2.0","id":1,"result":[{"name":"Example Tool","input":"Prompt","output":"Reply"}]} ``` Currently only a small set of actions and data is available but we plan to expand this with more exciting capabilities in the future! ## Installation Ensure python is installed on the system and then do the following: ``` git clone THIS_REPOSITORY pip install . ``` Setup the .env with an `API_KEY="YOUR_KEY"` ## Run Run the server with ``` python3 -m mcp_server ``` The server listens on port 8080