Installation and Setup Guide MCP Server

@ricardoborges

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AI 与智能体

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ricardoborges

关于 Installation and Setup Guide MCP Server

LLM chat app for integration tests using llama-stack-client, llama, Ollama, MCP, Tools

#mcp #chat-application #gradio #llm #ollama#llama-stack#mcp-server #mcp-client

Installation and Setup Guide MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "chatlab": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Installation and Setup Guide MCP Server 工具

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概览

What is Installation and Setup Guide?

This document provides step-by-step instructions for setting up the development environment and running the ChatLab application. It uses Ollama or Together.ai for LLM inference and LLama-Stack to manage the inference environment.

How to use Installation and Setup Guide?

Follow the installation steps sequentially: install Ollama or obtain a Together.ai API key, set up LLama-Stack using uv and a virtual environment, clone the repository, install dependencies via uv pip install -r myproject.toml, set environment variables (TAVILY_SEARCH_API_KEY, TOGETHER_API_KEY or DEFAULT_STACK="Ollama"), then run gradio main.py.

Key features of Installation and Setup Guide

Step-by-step guide for Ollama and Together.ai setup
Uses LLama-Stack to manage inference environments
Gradio-based web application interface
Supports local and cloud inference models

Use cases of Installation and Setup Guide

Setting up a local LLM environment with Ollama
Configuring cloud inference via Together.ai API
Running the ChatLab application with Gradio UI

常见问题

What prerequisites are needed?

Ollama must be installed (unless using Together.ai API) and the virtual environment must be activated correctly.

What dependencies are required?

Ollama or Together.ai API key, LLama-Stack, Python packages as listed in `myproject.toml`, and a Tavily search API key for search functionality.

Where does data live?

API keys are stored in a `.env` file (TAVILY_SEARCH_API_KEY, TOGETHER_API_KEY). Model inference runs either locally (Ollama) or on Together.ai servers.

What are known limitations?

The guide does not mention any specific limits; troubleshooting covers checking services and dependencies.

What transports or authentication are used?

No transports are mentioned. Authentication uses API keys for Together.ai and Tavily; local Ollama requires no external auth.

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