AI Service Platform

by Daniel1989

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GitHub

About

A cloud-ready service platform for AI-powered tool execution with Model Context Protocol (MCP) integration. It provides REST API endpoints, stateless design with persistent tool configuration, and supports horizontal scaling.

Explore

- Cloud Native Architecture
- REST API endpoints for all operations
- Stateless design with persistent tool configuration
- Horizontal scaling support

- Unified Tool Gateway
- Automatic discovery of MCP tools in servers/ directory

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name AI Service Platform
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

- Python 3.10+

1. Clone the repository:

git clone https://github.com/Daniel1989/mcp-server-cloud.git
cd mcp-server-cloud

2. Set up virtual environment:

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

3. Start development server:

FLASK_DEBUG=1 python flask.py

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "ai service platform": {
            "mcp-server-cloud": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

McpServers

{
    "mcp-server-cloud": {
        "command": "python",
        "args": [
            "-m",
            "venv",
            "venv"
        ]
    }
}

A cloud-ready service platform for AI-powered tool execution with Model Context Protocol (MCP) integration.

Key Features

- Cloud Native Architecture
- REST API endpoints for all operations
- Stateless design with persistent tool configuration
- Horizontal scaling support

- Unified Tool Gateway
- Automatic discovery of MCP tools in servers/ directory

Cloud Deployment

Prerequisites

- Python 3.10+

API Usage

Endpoints

List Available Tools

GET /tools

Execute Natural Language Query

POST /query
{
"query": "5+5",
}

Development Setup

1. Clone the repository:

git clone https://github.com/Daniel1989/mcp-server-cloud.git
cd mcp-server-cloud

2. Set up virtual environment:

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

3. Start development server:

FLASK_DEBUG=1 python flask.py

Resources

1. python-sdk. https://github.com/modelcontextprotocol/python-sdk 2. cline's prompt -- how to ask ai to select mcp server. https://github.com/cline/cline/blob/main/src/core/prompts/system.ts 3. remote mcp server https://github.com/sidharthrajaram/mcp-sse 4. https://actions.zapier.com/settings/mcp/
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