MCP Server Documentation

What are MCP Servers and Why Do You Need Them?

MCP (Model Control Protocol) servers act as bridges between AI language models and your development environment. They provide several key benefits:

• Enhanced Capabilities: MCP servers add tools and functions that aren't built into standard AI models, such as file system access, web searches, and code execution.
• Custom Workflows: They allow you to create specialized workflows tailored to your specific development needs.
• Integration: MCP servers connect seamlessly with popular IDEs like VSCode and Cursor, making AI assistance more accessible within your existing toolchain.
• Controlled Environment: They provide a secure and controlled way to extend AI capabilities without exposing sensitive data.

How MCP Servers Work

At a high level, MCP servers operate as middleware between your coding environment and AI language models:

1. Your IDE or application sends a request to the MCP server
2. The MCP server processes the request, potentially using additional tools or services
3. The server communicates with an AI model, enhancing the context or capabilities available
4. Results are returned to your application in a structured, usable format

This architecture allows for powerful extensions to AI capabilities while maintaining security and consistency.

Step 1. Clone the Repository

Begin by cloning the MCP server repository to your local machine.

git clone https://github.com/username/mcp-server-name.git
cd mcp-server-name

Step 2. Install Dependencies

Install all required dependencies for the MCP server.

npm install

Step 3. Configure the Server

Create or modify the configuration file according to your requirements. Most MCP servers use a config.json or .env file for configuration.

# Example for creating a .env file
cp .env.example .env
# Edit the .env file with your preferred text editor

Step 4. Start the Server

Launch the MCP server locally.

npm start

Step 5. Connect to the Server

With the server running, you can now connect your application to it.

# Example connection in Python
import requests

response = requests.post('http://localhost:8000/v1/execute', json={
    'command': 'your_command',
    'parameters': {}
})

Step 1. Install VSCode Extension

Open VSCode and navigate to the Extensions marketplace. Search for and install the MCP integration extension.

Step 2. Configure Extension Settings

Open VSCode settings and navigate to the MCP extension settings. Set the URL of your MCP server and any authentication credentials.

Step 3. Select an MCP Server

In the VSCode MCP extension panel, select the MCP server you wish to use from the dropdown menu of available servers.

Step 4. Use MCP Commands

Access MCP commands through the VSCode command palette (Ctrl+Shift+P or Cmd+Shift+P) by typing "MCP:" followed by the command name.

Step 5. Configure Shortcuts

For frequently used MCP operations, set up keyboard shortcuts in VSCode's keyboard shortcuts settings by mapping them to MCP extension commands.

Step 1. Run or Deploy Your MCP Server

Ensure your MCP server is up and running (locally or on a hosted platform) following the local instructions above.

Step 2. Open Cursor and Access Integrations

Launch Cursor and go to the integrations or settings panel where you can add external tools.

Step 3. Configure the MCP Server Connection

Add a new integration and enter the MCP server's endpoint URL along with any authentication or configuration parameters required by the server.

Cursor may allow you to test the connection—do so to confirm that the server's MCP endpoints are reachable.

Step 4. Explore and Use MCP Tools

Once the MCP server is connected, Cursor will display a list of available tools and resources provided by the server.

Use these tools within your coding workflow by selecting them from the integration menu. For example, you might invoke a command to run a shell operation or fetch repository data, as provided by the MCP server.

Step 5. Validate and Iterate

Test out a few commands or operations via Cursor to ensure that the MCP server's functionality integrates smoothly with your coding environment.

Adjust configuration settings if necessary and consult the MCP server's documentation for any troubleshooting.