This is a Model Context Protocol (MCP) server that provides image generation and web scraping capabilities for Windsurf.
MCP Server for Windsurf/Roocode is an MCP project maintained in the bananabit-dev/mcp repository. The maintainer describes its purpose as “This is a Model Context Protocol (MCP) server that provides image generation and web scraping capabilities for Windsurf”. Read the project documentation for the complete scope.
The project provides a local client configuration using /absolute/path/to/your/.venv/bin/python. Follow the repository’s build and installation steps before copying it, and replace example paths with the paths on your own computer.
The example declares PYTHONPATH, AIMLAPI_KEY, SGAI_API_KEY. Secret-looking values have been replaced with placeholders. Required and optional labels are shown only when the documentation states them.
Project documentation · Repository · Discovery listing. This profile records the public documentation checked on 2026-10-08.
{
"mcpServers": {
"bananabit-mcp": {
"command": "/absolute/path/to/your/.venv/bin/python",
"args": [
"-m",
"app.mcp_server"
],
"cwd": "/absolute/path/to/mcp",
"env": {
"PYTHONPATH": "/absolute/path/to/mcp",
"AIMLAPI_KEY": "YOUR_AIMLAPI_KEY",
"SGAI_API_KEY": "YOUR_SGAI_API_KEY"
}
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
| Variable | Description | Required |
|---|---|---|
| PYTHONPATH | Declared in the maintainer’s client configuration. | Check documentation |
| AIMLAPI_KEY | Declared in the maintainer’s client configuration. | Check documentation |
| SGAI_API_KEY | Declared in the maintainer’s client configuration. | Check documentation |
Retrieve public web pages as readable Markdown with the reference Fetch MCP server, including pagination for longer responses.
Use Firecrawl MCP to retrieve website content and extract information for research through Firecrawl’s API-backed web tools.
The original Chromium automation reference server — simple, screenshot-driven browser control.
Puppeteer-powered browser control that drives pages from the accessibility tree instead of pixels.
Automates browsers and APIs, enabling Large Language Models (LLMs) to interact with web pages for tasks like screenshot capture and JavaScript
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.