Cursor is, without a doubt, one of the most popular AI code editors. Known for its robust feature set and capabilities, it stands out from the competition. But do you know there’s a lot you can do to make your Cursor experience even better? That’s where the world of MCPs (Model Context Protocols) comes in. (learn how to create your own MCPs here) These servers can help perform tasks far beyond traditional coding, such as web scraping, browser automation, generative AI, experiment tracking, design integration, document conversion, and spreadsheet manipulation. The list goes on. And this article is all about that, showcasing seven of the best MCP servers for Cursor.
Let’s dig in.
7 Best MCP Servers For Cursor
1. Firecrawl MCP Server – Web Scraping
The Firecrawl MCP server enables Cursor to perform web scraping, extracting data from websites for research, data analysis, or content aggregation.
Why It’s Useful: Web scraping is essential for collecting data from the internet without manual effort. Firecrawl automates this process, allowing you to gather information for tasks like market research, competitor analysis, or building datasets for machine learning models. By integrating Firecrawl with Cursor AI, you can incorporate real-world data directly into your projects, saving time and enhancing your applications.
How to Set Up:
- Obtain an API key from Firecrawl.
- Install the server using the command: npx @firecrawl/mcp-server.
- Configure it in your .cursor/mcp.json file, following the instructions provided in the MCP documentation.
Example Use Case: Suppose you’re developing a price comparison tool for e-commerce products. Firecrawl can scrape product prices from multiple websites in real-time, allowing you to aggregate and analyze data directly within Cursor AI, ensuring your tool stays up-to-date.
Key Benefits:
- Automates data collection from dynamic websites.
- Supports research and data-driven development.
- Easy to configure with an API key.
2. Browserbase MCP Server – Cloud Browser Automation
The Browserbase MCP server allows Cursor to automate browser actions, such as testing, data extraction, and taking screenshots, in a cloud-based environment.
Why It’s Useful: Browser automation is critical for testing web applications, extracting data from dynamic sites, or performing complex interactions that require a browser. Browserbase provides a scalable, cloud-based solution, eliminating the need for local browser setups. This integration enables Cursor AI to handle repetitive web tasks efficiently, streamlining your development process.
How to Set Up:
- Get API credentials from Browserbase.
- Install the server using the provided node command.
- Add it to your .cursor/mcp.json configuration file.
Example Use Case: When building a web application, you can use Browserbase to automate end-to-end UI testing directly from Cursor AI. This ensures that your changes are thoroughly tested without leaving the editor, improving code quality and reducing bugs.
Key Benefits:
- Scalable cloud-based automation.
- Simplifies testing and data extraction.
- Integrates seamlessly with Cursor AI.
3. Magic MCP – Generative AI
The Magic MCP server provides access to generative AI models for tasks like image generation, text transformation, and code creation.
Why It’s Useful: Generative AI is transforming development by enabling rapid content creation and prototyping. Magic MCP leverages OpenAI’s models to generate images, transform text, or produce code snippets within Cursor AI. This is particularly valuable for developers who need to quickly iterate on ideas or create assets for their projects.
How to Set Up:
- Secure an API key from OpenAI.
- Install the server with npx @21st/magic-mcp.
- Configure it in Cursor AI’s MCP settings.
Example Use Case: If you’re designing a new application, Magic MCP can generate logo ideas or initial code structures for your project. You can refine these outputs within Cursor AI, speeding up the prototyping process.
Key Benefits:
- Accelerates prototyping with AI-generated content.
- Supports a wide range of generative tasks.
- Enhances creativity in development workflows.
4. Opik MCP – Experiment Tracking
The Opik MCP server integrates with Comet ML to track machine learning experiments, including metrics, parameters, and visualizations.
Why It’s Useful: For machine learning practitioners, tracking experiments is essential for iterating on models and understanding performance. Opik MCP allows you to log experiments directly from Cursor AI, keeping your development and experimentation workflows tightly integrated. This is especially useful for complex ML projects with multiple iterations.
How to Set Up:
- Create a Comet ML account.
- Install the server with npx @comet-ml/opik-mcp.
- Configure your .cursor/mcp.json file.
Example Use Case: While developing a new ML model, you can use Opik MCP to log experiments, compare model versions, and visualize performance metrics—all within Cursor AI. This ensures that your experimentation process is organized and efficient.
Key Benefits:
- Streamlines ML experiment tracking.
- Integrates with a leading ML platform.
- Keeps all project data in one place.
5. Figma Context MCP – Design Integration
The Figma Context MCP server enables Cursor to access and interact with Figma designs, extracting specifications and assets.
Why It’s Useful: Collaboration between designers and developers is critical for building user-friendly applications. Figma Context MCP brings Figma designs directly into Cursor AI, allowing developers to extract specifications, colors, and assets without switching tools. This ensures pixel-perfect implementations and reduces miscommunication.
How to Set Up:
- Obtain a Figma token from Figma’s developers page.
- Install the server with npx figma-context-mcp.
- Add it to your MCP configuration in Cursor AI.
Example Use Case: When implementing a new UI component, you can pull exact specifications from a Figma design into Cursor AI, ensuring your code matches the design intent perfectly and saving time on manual coordination.
Key Benefits:
- Bridges design and development workflows.
- Ensures accurate implementation of designs.
- Enhances collaboration with design teams.
6. Pandoc MCP – Document Conversion
The Pandoc MCP server facilitates document conversion between formats like markdown, PDF, HTML, and DOCX using Pandoc.
Why It’s Useful: Documentation is a vital part of software development, and converting between formats is often necessary for collaboration or distribution. Pandoc MCP integrates this powerful converter into Cursor AI, allowing you to transform documents on the fly without leaving your editor. This is particularly useful for creating professional documentation or sharing files with non-technical stakeholders.
How to Set Up:
- Ensure Pandoc is installed on your system.
- Install the server with npx mcp-pandoc.
- Configure it in your .cursor/mcp.json file.
Example Use Case: You can convert your project’s README from markdown to a PDF for distribution or to a DOCX for collaboration with non-technical team members, all within Cursor AI, streamlining your documentation process.
Key Benefits:
- Simplifies document format conversion.
- Supports a wide range of formats.
- Enhances documentation workflows.
7. Excel MCP Server – Spreadsheet Interaction
The Excel MCP server enables Cursor to read, modify, and analyze Excel files.
Why It’s Useful: Spreadsheets are widely used for data storage and analysis, especially in business and data science contexts. Excel MCP allows you to automate data processing, generate reports, or extract insights from Excel files directly within Cursor AI. This integration is ideal for developers working on data-heavy applications or automating business processes.
How to Set Up:
- Install the server with npx excel-mcp-server.
- Add it to your MCP configuration in Cursor AI.
Example Use Case: You can automate the generation of monthly reports by pulling data from an Excel file, performing calculations, and formatting the output within Cursor AI, ensuring your data workflows are as efficient as your coding tasks.
Key Benefits:
- Automates spreadsheet data processing.
- Integrates with common business tools.
- Enhances data-driven development.
The Bottom Line
Integrating MCP servers with Cursor AI goes beyond traditional code editing. Key servers include Firecrawl for web scraping, Browserbase for automation, Magic for generative AI, Opik for experiment tracking, Figma Context for design, Pandoc for document conversion, and Excel for spreadsheets. These tools enhance automation, design integration, and collaboration. If you want to learn how to create your own MCP server, you can follow this guide.
And if you want to know about the 10 best MCP servers in general, do so here.