What credentials are required?
Azure OpenAI API key, endpoint, API version, and model must be set in the `.azure.env` file.
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基本信息
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工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
This repository provides a demo environment for testing MCP (Model Context Protocol) Servers using Chainlit. It is intended for developers who want to experiment with MCP servers integrated into a chat interface, requiring only Azure OpenAI credentials to run.
Open the repository in VSCode and select the option to open in a Dev Container (no local installation needed). Add your Azure OpenAI credentials (API key, endpoint, API version, model) to the .azure.env file, then run chainlit run app.py -w. Through the chat interface, you can add MCP servers (e.g., filesystem) by providing a name and the corresponding npx command.
Azure OpenAI API key, endpoint, API version, and model must be set in the `.azure.env` file.
Through the chat interface, click the MCP Servers icon, provide a name and the command (e.g., `npx -y @modelcontextprotocol/server-filesystem /workspaces/chainlit-demo`).
No local installation; only Visual Studio Code with Dev Containers support and a running Docker environment.
It operates on the predefined workspace path `/workspaces/chainlit-demo` in the container.
Yes, you can add any MCP Server by specifying its name and the appropriate command. The README only illustrates the filesystem server.

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Model Context Protocol Servers
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