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Top MCP Clients to Supercharge Your AI Workflows in 2025

The Model Context Protocol (MCP) standardizes how AI agents interact with external tools and data sources. To leverage MCP in your projects, you need an MCP-compatible client—an application or library that handles the JSON-RPC calls for you. This guide explores the leading MCP clients today and shows how to connect each one to your MCP server.

Top MCP Clients to Supercharge Your AI Workflows in 2025

Figure: Top MCP Clients to Supercharge Your AI Workflows in 2025

Why Use an MCP Client?

  • Consistent interface
  • Rapid setup
  • Focus on AI, not plumbing

Prerequisites

  1. MCP server URL (HTTP or WebSocket endpoint)
  2. API key or token for authentication
  3. Network access to the server’s JSON-RPC interface

Engineers’ Essentials

These clients are battle-tested, integrate smoothly with popular editors, and power many production MCP deployments:

Claude Desktop

  • Platforms: Windows, macOS, Linux
  • Get started: Download the installer, then in Settings → Tools, add your MCP URL and API key.
  • Highlights: Built-in “Tools” sidebar, automatic method discovery, per-tool permission prompts.

Claude Code

  • Platforms: VS Code, JetBrains IDEs
  • Get started: Install the official plugin, then paste your MCP endpoint under the extension’s settings.
  • Highlights: Code-centric chat interface, inline editing and code execution, deep IDE integration.

Cursor

  • Platforms: Windows, macOS, Linux
  • Get started: Download from the official site, then in Settings → Integrations, enter your server URL and bearer token.
  • Highlights: AI-first code editor with chat, debugging, and one-click tool calls.

Cline

  • Platform: VS Code extension
  • Get started: Search “Cline” in the Extensions panel, install, then open the Cline sidebar → Connect → paste your MCP URL and key.
  • Highlights: File creation/editing, terminal commands, and web browsing—all from within VS Code.

Windsurf (Codeium)

  • Platforms: Windows, macOS, Linux
  • Get started:
    npm install -g windsurf-cli
    windsurf login
    windsurf mcp add
    
  • Highlights: Agent-driven IDE overlay, event-driven workflows, native streaming JSON-RPC.

Goose CLI

  • Platform: Command-line tool
  • Get started:
    brew install goose-cli   # macOS
    goose auth               # configure credentials
    goose mcp connect        # follow prompts
    
  • Highlights: Minimal, scriptable CLI for headless MCP calls in pipelines and CI.

Hidden Gems

These lesser-known clients pack powerful features and are worth watching in 2025:

Pro tip: Many of these support community-driven plugins and rapid iteration—perfect for early adopters and power users.

Agent-Building Frameworks

If you’re building your own autonomous agents or pipelines, these frameworks include MCP out of the box:

How to Choose the Right MCP Client

  1. Editor vs. standalone?
    IDE plugins vs. desktop apps vs. CLI tools.
  2. Automation level?
    Agentic platforms vs. simple command clients.
  3. Language & ecosystem?
    JS/TS SDKs, Emacs integration, etc.
  4. Security & compliance?
    OAuth/JWT support, fine-grained scopes, on-prem vs. cloud.

Quick Start

  1. Pick one client that aligns with your daily tools.
  2. Install & configure with your MCP server details.
  3. Verify connectivity by calling a simple method (e.g., list_tools).
  4. Build a demo: ask your AI to summarize a document, fetch calendar events, or trigger a CI job.

With the right MCP client in place, your AI assistant transforms from a passive chat companion into a fully action-capable partner—no custom integrations required.


Keywords

MCP clientModel Context ProtocolClaude DesktopClaude CodeCursorCline VS CodeWindsurf CLIGoose CLIContinue extension5ire assistantZed editorCopilot-MCPLibreChatGenAIScriptEmacs mcp.elotermSourcegraph CodyWitsyTheia AI/IDETester MCP clientagent-building frameworkscontextual AI workflowsAI tool integration2025 MCP trends