Weaviate MCP Server Template for Cursor IDE: Empowering AI Applications with Model Context Protocol

Overview: What is Weaviate MCP Server Template for Cursor IDE?

The Weaviate MCP Server Template for Cursor IDE is a robust, extensible solution designed to enable developers and integrators to create custom tools that can be seamlessly connected to Cursor IDE through the Model Context Protocol (MCP). This template provides a simple yet powerful foundation upon which you can build intelligent applications tailored to specific business needs. Whether deployed via Heroku, Docker, or directly in a local environment, this server ensures smooth integration with various AI clients such as Claude Desktop and Continue.

🔧 Core Features & MCP Capabilities

The Weaviate MCP Server Template is built on top of advanced Python frameworks, ensuring fast development cycles and robust performance. It supports multiple deployment methods, including Heroku for cloud scalability, Docker for containerized environments, and a traditional setup to run locally. The server provides core MCP capabilities such as standardized communication protocols, error handling mechanisms, and custom configuration options. These features facilitate seamless interaction with various AI clients.

⚙️ MCP Architecture & Protocol Implementation

The architecture of the Weaviate MCP Server Template is designed around the Model Context Protocol (MCP), which serves as a bridge between AI applications like Cursor IDE and proprietary tools or data sources. The protocol ensures consistent communication, enabling the server to provide real-time updates and responses through Server-Sent Events (SSE). Internally, the server leverages modern Python libraries for efficient handling of requests and responses.

The MCP implementation within this template includes comprehensive error handling, logging mechanisms, and configurable settings. These features allow developers to customize the behavior of the server according to their specific needs. Additionally, the template supports advanced security measures such as SSL encryption and user authentication.

🚀 Getting Started with Installation

Deploying via Heroku

1. Click "Deploy to Heroku" button:

2. Configure Cursor IDE:

   • Open Cursor Settings → Features
   • Add new MCP server and use the Heroku URL with /sse path (e.g., https://<your-app-name>.herokuapp.com/sse)

Docker Setup

1. Initial setup:

# Clone the repository
git clone https://github.com/kirill-markin/weaviate-mcp-server.git
cd weaviate-mcp-server

# Create environment file
cp .env.example .env

2. Build and run using Docker Compose:

# Build and start the server
docker compose up --build -d

# View logs
docker compose logs -f

# Check server status
docker compose ps

# Stop the server
docker compose down

3. Run tests:

uv run pytest -v

4. Test the server endpoint:

curl -i http://localhost:8000/sse

5. Connect to Cursor IDE:
   • Open Cursor Settings (gear icon)
   • Navigate to Features tab → MCP Servers
   • Click "Add new MCP server"
     • Name: Choose any name (e.g., "my-mcp-server-1")
     • Type: Select "sse" if connecting via Heroku, or "stdio" for local development
     • URL: Enter http://localhost:8000/sse or the Heroku URL

Traditional Setup

First, install the required tools:

# Install uv on macOS
brew install uv
# Or install via pip (any OS)
pip install uv

Start the server using either stdio transport (default) or SSE transport:

# Install the package with development dependencies
uv pip install -e ".[dev]"

# Using default stdio transport
uv run weaviate-mcp-server

# Using SSE transport on custom port
uv run weaviate-mcp-server --transport sse --port 8000

💡 Key Use Cases in AI Workflows

The Weaviate MCP Server Template is ideal for integrating various data sources and tools into AI workflows. For instance, a financial analyst can use the server to fetch real-time stock market data directly from Cursor IDE without coding. Conversely, an educational institution might deploy the server to provide personalized learning resources based on student performance metrics.

Consider these examples:

Example 1: Real-Time Stock Market Data Integration

• Scenario: A financial analyst in a trading firm needs access to up-to-the-minute stock prices.
• Implementation: The Weaviate MCP Server Template fetches real-time stock data from a dedicated API and serves it through an SSE endpoint. When the analyst queries this feed using Cursor IDE, they receive live updates.

Example 2: Personalized Learning Resources

• Scenario: An educational institution aims to provide personalized learning materials based on students' past performance.
• Implementation: The server gathers student data (grades, attendance) and cross-references it with educational content. Using MCPS, the system generates tailored study guides that are pushed directly to each student's Cursor IDE.

🔌 Integration with MCP Clients

The Weaviate MCP Server Template supports multiple MCP clients including Claude Desktop, Continue, and Cursor IDE. Below is a compatibility matrix highlighting supported features:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor IDE	❌	✅	❌	Tools Only

Note that while tools are fully supported, the Cursor IDE currently does not natively communicate with prompts.

📊 Performance & Compatibility Matrix

The Weaviate MCP Server Template offers high performance and broad compatibility across different environments. Key metrics for evaluation include latency, throughput, and concurrent connections. Here’s a sample configuration:

{
  "mcpServers": {
    "weaviate-mcp-server": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-weaviate"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

🛠️ Advanced Configuration & Security

Environment Variables

Available environment variables (set in .env):

• MCP_SERVER_PORT (default: 8000) - Port to run the server on
• MCP_SERVER_HOST (default: 0.0.0.0) - Host to bind the server to
• DEBUG (default: false) - Enable debug mode
• MCP_USER_AGENT - Custom User-Agent for website fetching

Security Measures

To ensure robust security, the template includes SSL encryption and token-based authentication mechanisms. You can configure these settings through environment variables or direct code modifications.

❓ Frequently Asked Questions (FAQ)

1. How does this MCP server enhance AI applications?

   • This server enhances AI applications by providing a standardized communication protocol, enabling seamless integration with various tools and data sources.

2. Can I use this template for both local development and cloud deployment?

   • Yes, the Weaviate MCP Server Template supports multiple deployment methods including Docker containers, traditional Python setups, and Heroku.

3. Which AI clients are compatible with this server?

   • This server is compatible with Cursor IDE, Claude Desktop, and Continue.

4. How do I set up an HTTPS endpoint for the server?

   • To enable HTTPS, you can use Certbot for automatic SSL certificate management during a Docker setup or configure Nginx as a reverse proxy.

5. Can I change the environment variables at runtime?

   • Yes, by using docker compose commands or modifying the .env file directly, you can adjust environment variables on-the-fly without stopping the server.

👨‍💻 Development & Contribution Guidelines

For developers interested in contributing to this project, please ensure the following:

1. Fork and Clone Repository:

   • Fork the Weaviate MCP Server Template from GitHub.
   • Clone your forked repository locally.

2. Set Up Your Local Environment:

   • Install required dependencies with pip install -e ".[dev]"
   • Configure environment variables in a local .env file.

3. Run Tests and Linting:

   • Use uv run pytest -v --reusedb --strict --flake8 --docstr-cov to run tests and static code analysis.
   • Ensure all tests pass before submitting a pull request.

4. Commit Changes with Descriptions:

   • Keep commit messages concise and descriptive, follow the standard Git flow.

5. Pull Request Guidelines:

   • Submit a detailed pull request and ensure it is reviewed by maintainers before merging.

🌐 MCP Ecosystem & Resources

Explore more resources within the MCP ecosystem:

• Smithery Installation
• Glama Server Review

For detailed documentation and community support, visit the official Model Context Protocol website.

By adopting the Weaviate MCP Server Template for Cursor IDE, developers can unlock new possibilities in AI application integration, enhancing productivity and innovation across various industries.