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MCP Server for Windsurf
Configuration
View docs{
"mcpServers": {
"yeakub108-mcp-server": {
"url": "https://example-mcp-endpoint.local/mcp",
"headers": {
"OPENAI_API_KEY": "YOUR_API_KEY"
}
}
}
}You have an AI-powered MCP server that integrates ready-made tools to assist with development tasks. It lets you run specialized AI-enabled agents that can architect code, review changes, read files, and analyze UI screenshots, all through a Cursor MCP client. This setup is designed as a practical, learning-focused demo to help you explore automated development workflows.
To use this MCP server, configure it in your MCP client so the client can call the serverβs tools from your Composer workflow. You will interact with the tools by asking for coding plans, UI analysis, or code reviews, and the AI will propose tool usage when appropriate. You can also request a specific tool by name or description, and the AI will present a prompt to run it. The tools include Code Architect for planning, Screenshot Buddy for UI analysis, Code Review for diffs-based reviews, and Read file / Read multiple files for file access.
Prerequisites: make sure you have Node.js installed on your machine and a functioning npm or yarn workspace.
Step 1. Install dependencies
npm install
# or
yarn installStep 2. Build the server
npm run buildStep 3. Configure the MCP client to load the server
{
"mcpServers": {
"mcp_server": {
"command": "node",
"args": [
"D:\\mpc-server\\build\\index.js"
]
}
}
}After adding the server, you should see your tools listed under the MCP server section in your client. If you donβt see them right away, refresh the MCP server list in your client. You can adjust how the tools are invoked by updating your clientβs rules or prompts to better steer the agent toward the available tools.
Generates plans and instructions for building features, outlining architecture and step-by-step actions for coding agents.
Analyzes UI design screenshots and feeds insights to the composer agent for UI-driven development.
Uses git diffs to trigger and guide code reviews, highlighting potential improvements.
Reads a single file to support targeted data analysis.
Reads multiple files to enable bulk data processing and analysis.