Best AI Editor for MCP: Claude Code vs Cursor vs VS Code vs Windsurf (2026)

Quick verdict

Not every AI editor handles MCP the same way. Some give you a CLI command that takes 10 seconds. Others require hand-editing JSON. Here is how the six major MCP-capable editors compare at a glance.

Read on for a detailed breakdown of each editor, or skip to the decision tree if you already know what you need.

What is MCP support in an editor?

MCP (Model Context Protocol) is the open standard that lets AI editors connect to external tools — databases, APIs, browsers, documentation services — through a single unified protocol. When an editor "supports MCP," it means you can configure MCP servers and the AI model inside that editor can discover and call the tools those servers expose. If you are new to MCP, read our full explainer on the Model Context Protocol.

The key differences between editors come down to three things: how you configure servers (CLI vs JSON vs YAML), where the config lives (global vs per-project), and what happens at runtime (auto-approval vs manual confirmation for tool calls). These details determine how fast you can get MCP working and how smoothly it runs day-to-day.

Editor-by-editor breakdown

Claude Code (CLI)

Config file: ~/.claude.json Transport: stdio, HTTP

Claude Code is Anthropic's official CLI for Claude. It runs entirely in your terminal — no GUI, no electron app, just a command-line interface backed by Claude's 200k-token context window.

Setup: Adding an MCP server takes one command:

claude mcp add context7 -- npx -y @upstash/context7-mcp@latest

That is it. The server is registered in ~/.claude.json and available immediately. No restart required for new sessions. You can also scope servers to specific projects using --scope project for per-directory configs.

Strengths:

• Fastest MCP setup of any editor (single CLI command)
• Largest context window (200k tokens) means more room for tool descriptions alongside your code
• Full shell access — the AI can run commands, read files, and use MCP tools in the same session
• Project-scoped and global configs give you flexibility
• Built by Anthropic, the creators of MCP — tightest integration

Limitations:

• Terminal only, no visual GUI
• No syntax highlighting or inline code completion in the traditional sense
• Requires comfort with CLI workflows
• API-based pricing can be unpredictable for heavy usage

Best for: Developers who live in the terminal, power users who want maximum control, and anyone who values setup speed over visual interfaces.

Cursor

Config file: .cursor/mcp.json (per-project) Transport: stdio, HTTP

Cursor is a VS Code fork purpose-built for AI-assisted coding. It combines a familiar IDE layout with deeply integrated AI features including chat, inline edits, and tab completion.

Setup: Create a .cursor/mcp.json file in your project root:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}

Cursor picks up the config automatically. You can also configure servers through Settings > MCP in the UI.

Strengths:

• Familiar VS Code-based interface with AI superpowers
• Project-level MCP configs mean teams can share server setups via version control
• Composer mode lets the AI make multi-file edits using MCP tools for context
• Large and active community with frequent updates
• Agent mode with automatic tool approval available

Limitations:

• MCP config is per-project (no global config without workarounds)
• Some MCP features still marked as experimental
• Pro plan required for most useful AI features
• 128k context window leaves less room than Claude Code when running many servers

Best for: Developers who want a full IDE experience with AI built in, and teams that need to share MCP configs across a project.

VS Code (GitHub Copilot)

Config file: .vscode/settings.json (under mcp section) Transport: stdio, HTTP

VS Code added native MCP support through GitHub Copilot's agent mode. If you already use VS Code and Copilot, MCP works without installing anything new.

Setup: Add an mcp section to your .vscode/settings.json:

{
  "mcp": {
    "servers": {
      "context7": {
        "type": "stdio",
        "command": "npx",
        "args": ["-y", "@upstash/context7-mcp@latest"]
      }
    }
  }
}

Note: VS Code requires an explicit type field ("stdio" or "http"), which other editors infer automatically.

Strengths:

• Zero migration cost if you already use VS Code
• Massive extension ecosystem complements MCP servers
• MCP configs can be committed to the repo for team sharing
• Copilot agent mode integrates MCP tools naturally
• The $10/month Copilot plan is the cheapest paid option

Limitations:

• MCP support requires Copilot agent mode (not available in the free tier's basic chat)
• Config format slightly different from other editors (requires type field, uses servers key instead of mcpServers)
• MCP feature set still catching up to dedicated AI editors
• Agent mode less polished than Cursor or Claude Code for complex multi-step tasks

Best for: Developers already invested in the VS Code ecosystem who want MCP without switching editors.

Windsurf

Config file: ~/.codeium/windsurf/mcp_config.json (global) Transport: stdio, HTTP

Windsurf (by Codeium) is another VS Code-based AI editor. It differentiates with a generous free tier and a "Cascade" agent that chains multiple AI actions together.

Setup: Edit the global config file at ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}

Strengths:

• Generous free tier makes it the most accessible option for trying MCP
• Global config means servers are available across all projects automatically
• Cascade agent handles multi-step tasks well with MCP tools
• Clean, opinionated UI that is easy to get started with

Limitations:

• Global-only config (no built-in per-project MCP configs)
• Uses serverUrl instead of url for HTTP transport (minor config difference)
• Smaller community than Cursor or VS Code
• Less documentation on advanced MCP usage patterns

Best for: Developers who want a free or low-cost entry point into AI-assisted coding with MCP, and those who prefer a global server setup.

Claude Desktop

Config file: ~/Library/Application Support/Claude/claude_desktop_config.json Transport: stdio, HTTP

Claude Desktop is Anthropic's GUI chat application. It is not a code editor — it is a conversational AI interface that happens to support MCP. This makes it useful for non-coding MCP workflows and for testing servers before adding them to your editor.

Setup: Edit the config file at the path above (macOS). On Windows, the path is %APPDATA%/Claude/claude_desktop_config.json.

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}

Restart Claude Desktop after editing the config.

Strengths:

• Full 200k-token context window (same as Claude Code)
• Visual conversation interface with artifact rendering
• Good for non-coding MCP use cases (research, data analysis, content generation)
• Easy to test and debug MCP servers before deploying to your editor
• Supports the same config format as most other clients

Limitations:

• Not a code editor — no file tree, no inline editing, no terminal
• No project-level config (global only)
• Requires app restart when changing MCP config
• Pro subscription required for high-volume usage

Best for: Non-developers who want MCP tools in a chat interface, and developers who want a sandbox for testing MCP server configs.

Continue

Config file: ~/.continue/config.yaml Transport: stdio, HTTP

Continue is the only fully open-source option in this list. It runs as a VS Code or JetBrains extension and supports any LLM provider — OpenAI, Anthropic, local models via Ollama, and more.

Setup: Add servers to ~/.continue/config.yaml:

mcpServers:
  - name: context7
    command: npx
    args:
      - -y
      - "@upstash/context7-mcp@latest"

Strengths:

• Fully open source (Apache 2.0 license)
• Works with any LLM, not just Claude or GPT
• YAML config is arguably more readable than JSON
• Runs inside VS Code or JetBrains (use your existing IDE)
• No vendor lock-in

Limitations:

• Context window depends on the model you choose (varies widely)
• YAML config format differs from all other editors (not directly portable)
• Smaller team and slower release cadence than funded competitors
• MCP integration less battle-tested than Claude Code or Cursor
• Requires more manual configuration for optimal performance

Best for: Developers who prioritize open source, want to use local or custom models, or work in JetBrains IDEs.

Full comparison table

Which editor should you pick?

Use this decision tree based on your situation:

"I live in the terminal and want the fastest setup." Go with Claude Code. One CLI command per server, 200k context, no GUI overhead. Pair it with the Indie Hacker stack and you are productive in under a minute.

"I want a full IDE with the best AI features." Go with Cursor. It has the most mature AI coding experience, strong community, and project-level MCP configs that work well for teams. Check out the Frontend Developer stack for a ready-made config.

"I already use VS Code and do not want to switch." Stay with VS Code + Copilot. Enable agent mode, add your MCP config to .vscode/settings.json, and keep your existing workflow. Cheapest paid option at $10/month.

"I want to try MCP without paying anything." Start with Windsurf (free tier) or Continue (fully free and open source). Both support MCP and let you experiment before committing to a paid plan.

"I use JetBrains (IntelliJ, WebStorm, PyCharm)." Continue is your best option. It is the only MCP-capable tool with a JetBrains extension.

"I want to test MCP servers before adding them to my editor." Use Claude Desktop as a sandbox. Configure a server, test it in the chat interface, then copy the config to your editor of choice.

"I want to use local or custom models." Continue is the only option that supports arbitrary LLM providers including local models via Ollama.

How to switch editors

MCP configs are mostly portable between editors. The core structure — server name, command, args, env vars — is the same everywhere. The differences are small:

1. JSON key name: Most editors use mcpServers. VS Code uses servers.
2. Type field: VS Code requires an explicit type: "stdio" or type: "http". Others infer it.
3. HTTP URL field: Windsurf uses serverUrl. Others use url.
4. Config format: Continue uses YAML instead of JSON.

If you switch from Cursor to Claude Code, your server entries transfer with minimal changes. The StackMCP config generator handles this automatically — select your servers, pick a target editor, and get the exact config file you need.

You do not need to reinstall MCP servers when switching editors. The servers themselves are npm packages or binaries that run the same way regardless of which editor starts them.

Next steps

• Browse curated MCP stacks — Pre-built server combinations for specific roles and frameworks
• Explore all MCP servers — Full directory with quality scores, token estimates, and download stats
• Generate your config — Pick servers, choose your editor, copy the config
• What is MCP? — Full explainer on the Model Context Protocol
• How to cut MCP token costs in half — Optimize your context window when running multiple servers