MCP (Model Context Protocol) Server
Description
# MCP (Model Context Protocol) Server ## Project Structure ``` ├── client.py # Client-side interaction script ├── server.py # Main MCP server implementation ├── pg_connect.py # PostgreSQL database connection ├── lm_config.py # Language model configuration │ ├── .env.example #…
About
# MCP (Model Context Protocol) Server ## Project Structure ``` ├── client.py # Client-side interaction script ├── server.py # Main MCP server implementation ├── pg_connect.py # PostgreSQL database connection ├── lm_config.py # Language model configuration │ ├── .env.example # Example environment configuration ├──…
Details
- Author
- VajraM-dev
- Downloads
- 131
- Categories
- Database
Jump to
- Secure configuration management
- PostgreSQL database integration
- Multi-provider AI model support
- Flexible communication transport
- Extensible tool registration
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:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
MCP (Model Context Protocol) ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Clone the repository, create a Python virtual environment, install dependencies, configure environment by copying .env.example to .env.dev and filling in database and API credentials, then run python server.py for the server and python client.py for client interaction.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp (model context protocol) server": {
"Postgres-MCP-Server-With-SSE-Transport": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}
}McpServers
{
"Postgres-MCP-Server-With-SSE-Transport": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}MCP (Model Context Protocol) Server
Project Structure
├── client.py # Client-side interaction script
├── server.py # Main MCP server implementation
├── pg_connect.py # PostgreSQL database connection
├── lm_config.py # Language model configuration
│
├── .env.example # Example environment configuration
├── .env.dev # Development environment configuration
├── requirements.txt # Project dependencies
└── .gitignore # Git ignore file
Prerequisites
- Python 3.10+ - PostgreSQL - API access to AI providers (Anthropic, Google)Installation
1. Clone the Repository
git https://github.com/VajraM-dev/Postgres-MCP-Server-With-SSE-Transport.git
2. Create Virtual Environment
python -m venv venv
source venv/bin/activate # On Windows, use venv\Scripts\activate
3. Install Dependencies
pip install -r requirements.txt
4. Configure Environment
1. Copy.env.example to .env.dev
2. Fill in the required configuration:
cp .env.example .env.dev
nano .env.dev # or use your preferred text editor
Configuration Parameters
-POSTGRES_USERNAME: PostgreSQL database username
- POSTGRES_PASSWORD: PostgreSQL database password
- POSTGRES_DB_NAME: Database name
- POSTGRES_HOST: Database host
- POSTGRES_PORT: Database port
- MCP_NAME: Server name
- MCP_HOST: Server host
- MCP_PORT: Server port
- TRANSPORT: Communication transport (sse/stdio)
- ANTHROPIC_API_KEY: Anthropic API key
- GOOGLE_API_KEY: Google API key
- USE_PROVIDER: Default AI provider
Running the Server
Development Mode
python server.py
Client Interaction
python client.py
Key Features
- 🔒 Secure configuration management - 🗃️ PostgreSQL database integration - 🤖 Multi-provider AI model support - 📡 Flexible communication transport - 🛡️ Extensible tool registrationSupported AI Providers
- Anthropic (Claude models) - Google (Gemini models)Tools and Endpoints
Available Tools
-list_tables(): Retrieve database tables
- Custom tools can be easily added via decorators
Endpoints
-/sse: Server-Sent Events endpoint
- Customizable routing and tool registration
Extending the Framework
Adding New Tools
@app.tool()
def custom_tool():
"""Custom tool implementation"""
# Your tool logic here
Configuring AI Providers
Modifylm_config.py to add or configure new AI providers.Sign in to leave a review
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