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Advanced MCP Server

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Rahii123

Provides real-time weather alerts from the National Weather Service, news search capabilities via NewsAPI, and safe local directory exploration for AI assistants.

PublisherRahii123
Repositorymcp
LanguagePython
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Transport typestdio
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LicenseMIT
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  • Connect tools to AI workflows

    Advanced MCP Server exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    0 stars and 1 forks from the linked repository.

๐Ÿš€ Advanced MCP Server

A professional Model Context Protocol (MCP) server built with Python and FastMCP. This server extends AI capabilities by providing real-time data and local system access.

โœจ Features

  • ๐ŸŒฆ๏ธ Weather Alerts: Fetches active US weather alerts from the National Weather Service.
  • ๐Ÿ“ฐ News Search: Real-time news searching using the NewsAPI.
  • ๐Ÿ“ Directory Explorer: Allows the AI to list and explore local system directories safely.
  • ๐Ÿ” Secure Secrets: Uses .env for safe API key management.

๐Ÿ› ๏ธ Getting Started

Prerequisites

  • Python 3.10+
  • uv (Recommended)

Installation

  1. Clone the repository:
    bash
    git clone https://github.com/Rahii123/mcp.git
    cd mcp
  2. Install dependencies:
    bash
    uv sync

Setup

Create a .env file in the root directory and add your NewsAPI key:

env
NEWS_API_KEY=your_actual_key_here

๐Ÿš€ Running the Server

Run directly with uv:

bash
uv run server.py

๐Ÿงช Testing Your Server

We have provided two separate clients for testing:

๐Ÿ  1. Local Testing (Stdio)

Use this when you are developing on your own machine.

bash
uv run client_local.py

This starts the server as a background process and communicates directly.

๐ŸŒ 2. Online Testing (SSE)

Use this after you have deployed your server to the web (e.g., Railway).

bash
uv run client_online.py

This asks for your deployment URL and connects over the internet.


โ˜๏ธ Deployment to Railway (Step-by-Step)

1. Push to GitHub

Ensure all your changes are committed and pushed to your GitHub repository:

bash
git add .
git commit -m "Prepare for deployment"
git push origin main

2. Connect to Railway

  1. Go to Railway.app and log in.
  2. Click + New Project > Deploy from GitHub repo.
  3. Select your mcp repository.

3. Configure the Service

  1. Environment Variables:
    • Go to the Variables tab in Railway.
    • Add NEWS_API_KEY: (Your actual NewsAPI Key)
  2. Start Command:
    • Railway should automatically detect pyproject.toml, but if needed, set the start command to:
      bash
      uv run server.py
  3. Networking:
    • Railway will automatically detect the port from the $PORT environment variable. Ensure your server.py is using mcp.run(transport='sse') (I've already configured this for you).

4. Fetch your URL

Once the build is finished, Railway will provide a public URL (e.g., https://mcp-production.up.railway.app). The MCP endpoint will be at: https://your-app-url.up.railway.app/sse


Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "advanced-mcp": {
      "command": "uvx",
      "args": [
        "advanced-mcp"
      ],
      "env": {
        "NEWS_API_KEY": "your_actual_key_here"
      }
    }
  }
}

Use Advanced MCP Server MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Advanced MCP Server is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Advanced MCP Server as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Advanced MCP Server MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "advanced-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "advanced-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Advanced MCP Server MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Advanced MCP Server MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Advanced MCP Server to help me with this task?
Advanced MCP Server
Sure. I read it.
Here is what I found using Advanced MCP Server.

Frequently asked questions

What is the Advanced MCP Server MCP server used for?

Advanced MCP Server is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Advanced MCP Server MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Advanced MCP Server with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Advanced MCP Server MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Advanced MCP Server connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Advanced MCP Server MCP to TypingMind?

Advanced MCP Server runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Advanced MCP Server MCP provide in TypingMind?

Advanced MCP Server exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Advanced MCP Server MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Advanced MCP Server requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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