Top MCP Servers for Cursor Integration

Model Context Protocol
11 min read

Best MCP Servers for Cursor

MCP servers enhance Cursor by integrating AI-powered toolkits that boost development efficiency. The best MCP servers provide connectivity to external data sources, automating workflows inside Cursor’s IDE. This article outlines how to add MCP servers to Cursor, highlights top servers, and shares tips to optimize use.

Understanding MCP and Cursor Integration

MCP (Model Context Protocol) servers act as bridges between Cursor and external services or APIs. Cursor hosts these MCP clients and servers, enabling seamless AI tooling. This setup allows developers to integrate specialized functionalities such as web scraping, database queries, APIs, and automation directly within their workspace.

How to Add MCP Servers to Cursor

Prerequisites

  • Install Node.js for running MCP servers with npx.
  • Install Python and UV for running Python-based MCP servers.
  • Ensure proper installation per your operating system (Windows/macOS).

Configuration Locations

MCP servers can be configured either globally or per project:

  • Project Configuration: Place a .cursor/mcp.json file inside the project directory to keep servers project-specific.
  • Global Configuration: Place a ~/.cursor/mcp.json in the home directory for access across all Cursor workspaces.

Supported Transport Types

Transport TypeDescriptionCommunication
stdioLocal execution; Cursor manages processstdout & stdin over shell commands
SSE (Server-Sent Events)Local or remote execution; user-managedNetwork via HTTP URL to /sse endpoint

MCP Server Configuration Format

Cursor uses JSON to define MCP servers. Here is a common structure:

{
"mcpServers": {
"server-name": {
"command": "run-command",
"args": ["arg1", "arg2"],
"env": {
"API_KEY": "your_api_key"
}
}
}
}

Examples:

  • Node.js MCP server using npx:
{
"mcpServers": {
"github-tools": {
"command": "npx",
"args": ["-y", "mcp-github"],
"env": {
"GITHUB_TOKEN": "your-github-token"
}
}
}
}
  • Python MCP server using UV:
{
"mcpServers": {
"database-query": {
"command": "uv",
"args": ["run", "python", "-m", "mcp_database_tool"],
"env": {
"DB_CONNECTION_STRING": "your-connection-string"
}
}
}
}
  • SSE-based MCP server:
{
"mcpServers": {
"remote-service": {
"url": "http://example.com:8000/sse"
}
}
}

Example: Setting Up a Search Service

Create a shell script that changes directories, sets environment variables, and runs the server command. Point your Cursor MCP configuration to this script for controlled execution.

!/bin/bash
TARGET_DIR=/path/to/your-server-directory
cd ${TARGET_DIR}
export API_KEY=your-api-key
export PYTHONIOENCODING=utf-8
uv --directory $PWD run your-server-command

Using MCP Tools Inside Cursor

Cursor’s Composer Agent automatically recognizes and uses listed MCP tools when relevant. You can explicitly direct the agent to use a specific tool. Approval prompts display by default, but enabling “Yolo mode” allows tools to run without approvals. Results appear in chat with invocation details.

Top MCP Servers to Use with Cursor

1. Firecrawl MCP Server

Firecrawl is a leading web scraping MCP server with over 1,800 GitHub stars, offering robust direct web content access from Cursor. It excels for competitive analysis, machine learning data gathering, content monitoring, and documentation extraction.

Main Features

  • Basic content scraping from any URL
  • Batch scraping with rate limiting
  • Search queries with extraction from results
  • Crawling supporting depth and domain constraints
  • Structured data extraction with intelligent parsing

Adding Firecrawl to Cursor

Obtain your API key from firecrawl.dev, then add this to your `.cursor/mcp.json` file:

{
"mcpServers": {
"firecrawl": {
"command": "npx",
"args": ["-y", "@firecrawl/mcp-server"],
"env": {
"FIRECRAWL_API_KEY": "your_api_key_here"
}
}
}
}

2. Calculator MCP Server

This server performs precise mathematical operations, enriching LLMs with numerical accuracy. Useful for data analysis and computational workflows.

3. User Feedback MCP Server

Supports human-in-the-loop interventions in AI workflows inside Cursor, improving results with real-time feedback and collaboration.

4. HackMD MCP Server

Integrates collaborative note-taking with Cursor’s AI assistants, streamlining documentation tasks alongside coding.

Additional Noteworthy MCP Servers

  • Puppeteer MCP Server: Enables headless browser web automation and scraping using Chrome.
  • ALAPI MCP Tools: Offers access to thousands of pre-built cloud API tools including social media and maps.
  • Browserbase and Magic MCP Servers: Designed for automation and generative AI tasks within Cursor.
  • Cloudflare MCP Server: Provides API access to Cloudflare for DNS and security operations.

Managing MCP Servers Effectively

Cursor lets you toggle automatic tool execution via “Yolo mode,” reducing interruptions. You can maintain separate MCP configurations globally or per workspace depending on your workflow needs, optimizing resource use and context relevance.

Summary of Key Takeaways

  • MCP servers provide powerful external integrations enhancing Cursor’s IDE capabilities.
  • Configure MCP servers either globally or per project using JSON files.
  • Cursor supports local (stdio) and remote (SSE) MCP server transports.
  • Installation requires Node.js (npx) or Python (UV) environments.
  • Firecrawl MCP server stands out for integrated, efficient web scraping in Cursor.
  • Additional servers cover calculators, feedback loops, note-taking, and browser automation.

Best MCP Servers for Cursor: Unlocking the Power of AI-Driven Development

If you’re diving into the world of Cursor, an AI-powered IDE, and wondering how to supercharge it, the answer lies in integrating the best MCP servers for Cursor. These servers link external APIs, data sources, and tools to Cursor’s versatile AI clients, enhancing your workflow and productivity. Whether you’re aiming to scrape the web, automate tasks, or connect sophisticated cloud services, adding MCP servers to Cursor is the secret sauce.

Let’s unravel the magic behind these servers, how to set them up, and which ones are worthy of your developer toolkit. Ready to upgrade your Cursor experience? Let’s jump in.

What’s MCP Anyway, and How Does It Mesh With Cursor?

First things first: MCP stands for Model Context Protocol. It’s a lightweight protocol allowing AI clients inside IDEs like Cursor to interact seamlessly with external servers that pull data, execute commands, or integrate complex APIs.

Imagine Cursor as your development hub or “host” that orchestrates MCP clients (your AI tools) and these MCP servers, like little digital helpers that bring extra data and capabilities right into your coding playground. For example, through MCP, Cursor can talk to an external web scraping server or a database query engine without you manually fetching or coding complex API calls.

Popular AI hosts like Cursor, Windsurf, Cline, and Claude Desktop all support MCP integration, enabling developers to harness powerful external services directly from their IDE.

How to Add MCP Servers in Cursor: Step by Step

Installing and configuring MCP servers for Cursor might sound daunting, but it’s quite straightforward. Here’s how to nail it:

  1. Prerequisites Installation: Most MCP servers rely on Node.js with the handy npx command or Python with uv (UltraViolet). So, install Node.js & npx or Python & uv on your machine first. Installation guides are friendly for Windows and macOS users.
  2. Configure MCP Servers: MCP configurations live in JSON files. You can keep settings project-specific by placing a .cursor/mcp.json file inside your project folder. Or go global with ~/.cursor/mcp.json in your home directory so MCP servers are available everywhere.
  3. Choose Transport Type: Cursor supports two communication channels for MCP servers:
    • stdio Transport: The server runs locally, communicating over standard input/output streams using shell commands. This is automatically managed by Cursor.
    • SSE Transport: The server runs either locally or remotely and communicates via Server-Sent Events over a network URL (typically to /sse). You manage and deploy this yourself.
  4. Write Configuration JSON: Your MCP server entry might look like this for Node.js: { mcpServers: { firecrawl: { command: npx, args: [-y, ‘@firecrawl/mcp-server’], env: { FIRECRAWL_API_KEY: ‘your_api_key_here’ } } } } Or for a Python-based MCP server: { mcpServers: { database-query: { command: uv, args: [‘run’, ‘python’, ‘-m’, ‘mcp_database_tool’], env: { DB_CONNECTION_STRING: ‘your_connection_string’ } } } }

You can also configure MCP with just a URL for SSE transports:

{
mcpServers: {
remote-service: {
url: ‘http://example.com:8000/sse’
}
}
}

Example: Setting Up a Search Service MCP Server

Want to run a local custom MCP server? Say you have a search backend script. You can wrap its startup within a shell script like this:

!/bin/bash

TARGET_DIR=/path/to/your-server-directory
cd ${TARGET_DIR}
export API_KEY=your-api-key
export PYTHONIOENCODING=utf-8
uv –directory $PWD run your-server-command

Then tell Cursor to run this script as your MCP server:

{
mcpServers: {
search-service: {
command: ‘/path/to/script.sh’
}
}
}

This script neatly sets up environment variables, changes directories, and runs your server securely and predictably. It’s also easier to troubleshoot.

Best MCP Servers You Should Definitely Try with Cursor

Let’s highlight some top MCP servers that can massively boost Cursor’s capabilities:

1. Firecrawl MCP Server – Your Web Scraping Powerhouse

With over 1.8k stars on GitHub, Firecrawl is by far the most popular MCP server available. It brings highly specialized web scraping directly into Cursor, giving developers unprecedented access to web content without leaving the editor.

  • Features:
    • Scrape pretty much any URL and convert content to markdown-friendly formats.
    • Batch scrape with customizable rate limiting.
    • Deep crawling with domain or depth limits, great for structured data extraction.
    • Search functionality for querying the web and extracting snippets or data.
    • Monitor content changes over time so you never miss updates.
  • Benefits: Perfect for research, competitor analysis, building training datasets for ML, and dev documentation.
  • Setup: Just get your API key at firecrawl.dev and add it to Cursor’s MCP config!

2. Calculator MCP Server – Precision Math on Demand

Developers often need exact math beyond what language models can safely guess. Calculator MCP servers empower LLMs with accurate arithmetic capabilities, reducing errors in financial apps, scientific coding, or anywhere numbers matter.

3. User Feedback MCP Server – Human-in-the-Loop AI Workflows

Ever wanted your AI assistant in Cursor or Cline to pause for human approval or enhancements? User Feedback MCP servers enable that smooth collaboration, blending automation with human judgment for better results.

4. HackMD MCP Server – Collaborative Docs Meet AI

For teams using HackMD for shared notes and documentation, this MCP server merges live document collaboration with AI helpers, creating an intelligent workspace for writing, reviewing, and editing documents.

5. Puppeteer MCP Server – Browser Automation and Scraping

This server uses headless Chrome automation to simulate real browser interactions, ideal for complex scraping tasks requiring JavaScript rendering, form submissions, or site navigation. Great for sophisticated data projects.

6. ALAPI MCP Tools – API Wonderland with Thousands of Interfaces

Imagine calling hundreds of API endpoints through a single MCP server. ALAPI offers 3,000+ pre-built cloud tools for data from websites, e-commerce stores, social networks, search engines, maps, and more.

With ALAPI MCP integrated, Cursor turns into a Swiss Army knife for data extraction and integration.

Managing MCP Servers Smoothly in Cursor

Cursor makes MCP tool usage intuitive and flexible. For example, it can prompt you to approve every tool run or enable a “Yolo mode” where your assistant runs MCP tools automatically without asking. Responses show in your chat window with details so you stay informed.

Add new MCP servers by editing your project or global mcp.json configurations. Cursor supports quick deployments, especially for Node.js TypeScript MCP tools via its CLI, making it developer-friendly to extend your AI workflows.

Where to Discover More MCP Servers?

Want to explore a treasure trove of MCP servers? Check out MCPServerFinder.com, the largest directory for Cursor-compatible MCP servers. They list hundreds of servers tailored for work, personal projects, or pure curiosity about AI’s evolution.

It’s a great place to browse, try, and marvel how far AI tooling has come.

Final Thoughts: Why You Should Care About MCP Servers for Cursor

Best MCP servers for Cursor aren’t just fancy add-ons—they’re transformative tools that expand your AI assistant’s powers beyond the IDE walls. You get real-time web data, precision calculations, human feedback loops, collaborative documentation, and robust automation in a single seamless environment.

Integrating MCP servers means spending less time juggling APIs, scraping data manually, or switching between apps. You stay focused on building, prototyping, and innovating faster.

So, whether you’re a curious developer or a seasoned engineer, setting up MCP servers in Cursor deserves a place in your workflow. The blend of easy configuration, powerful tools like Firecrawl, and smooth AI integration makes it a practical game-changer.

Quick Action Plan for Beginners

  1. Install Node.js & Python UV environments on your machine.
  2. Create or edit your project’s .cursor/mcp.json file to define MCP servers.
  3. Start with the Firecrawl server to unlock powerful web scraping right inside Cursor.
  4. Experiment with other MCP servers such as Calculator and User Feedback to enhance your AI interactions.
  5. Enable “Yolo mode” if you want seamless automatic tool execution without prompts (use cautiously!).
  6. Explore MCPServerFinder.com for more fascinating MCP servers.

With these steps, your Cursor IDE will become a highly efficient AI-enhanced development environment, ready for the challenges of modern coding and data workflows.

Have You Tried Any MCP Servers With Cursor Yet? What Has Been Your Experience? Drop a comment or share your stories—because we all learn better together!

What are MCP servers and how do they enhance Cursor?

MCP servers act as bridges between AI clients and external data sources. Integrating them with Cursor lets developers use AI tools alongside live data inside the IDE, boosting productivity and capabilities.

How do you configure MCP servers for Cursor?

MCP servers configuration is done via a JSON file stored either in the project at .cursor/mcp.json or globally at ~/.cursor/mcp.json. This file defines server commands, arguments, and environment variables for each MCP server.

What transport methods does Cursor support for MCP servers?

Cursor supports stdio and SSE transports. Stdio runs servers locally via command-line communication. SSE allows running servers locally or remotely, communicating over a network through an HTTP endpoint.

How can I add the Firecrawl MCP server to Cursor?

Get an API key from Firecrawl’s website. Then add Firecrawl’s configuration to your MCP JSON file with the command npx -y @firecrawl/mcp-server and your API key under environment variables. This integrates web scraping features into Cursor.

What prerequisites are needed before adding MCP servers to Cursor?

You must install Node.js with npx or Python with UV, depending on the server you plan to run. These provide the runtime and package execution needed to launch MCP servers from Cursor.

Can MCP servers run remotely and still work with Cursor?

Yes, via the SSE transport, MCP servers can run on remote machines. Cursor connects to them using the server’s URL targeting the /sse endpoint, enabling network communication with remote MCP services.

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