developer-tools

VS Code

block

by block

Seamlessly interact with Visual Studio Code for coding, file diffing, project navigation, and command execution using ad

Enables direct interaction with VS Code through bidirectional communication, providing tools for file diffing, project navigation, shell command execution, and editor information retrieval for seamless coding assistance.

github stars

76

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Bidirectional VS Code integrationDiff preview with user approvalWorks with Claude Desktop and Goose

best for

  • / Developers using AI coding assistants like Claude or Goose
  • / Code review and editing workflows with AI assistance
  • / Project setup and navigation through AI chat

capabilities

  • / Execute shell commands in VS Code terminal
  • / Create and preview file diffs before applying changes
  • / Open files and projects in VS Code editor
  • / Navigate between active and context-marked tabs
  • / List and switch between available projects
  • / Check extension connectivity status

what it does

Enables AI assistants to directly control VS Code through bidirectional communication, allowing file editing, project navigation, and shell command execution from your AI chat.

about

VS Code is a community-built MCP server published by block that provides AI assistants with tools and capabilities via the Model Context Protocol. Seamlessly interact with Visual Studio Code for coding, file diffing, project navigation, and command execution using ad It is categorized under developer tools. This server exposes 9 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install VS Code in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

Apache-2.0

VS Code is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

VSCode MCP

This monorepo contains the VSCode MCP Server and its companion VSCode Extension, which together enable AI agents and assistants, like Goose or Claude, to interact with VSCode through the Model Context Protocol.

Project Structure

vscode-mcp/
├── server/    # MCP server implementation
└── extension/ # VS Code extension

Quick Start

  1. Install the MCP Server
npx vscode-mcp-server install
  1. Install the MCP Extension

MCP Extension

Configuration

Goose Desktop Setup

Goose Settings

  • ID: code-mcp
  • Name: VS Code
  • Description: Allows interaction with VS Code through the Model Context Protocol
  • Command: npx vscode-mcp-server

Claude Desktop Setup

Add this to your Claude Desktop config file (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "vscode-mcp-server": {
      "command": "npx",
      "args": ["vscode-mcp-server"],
      "env": {}
    }
  }
}

Available Tools

The Code MCP server provides the following tools for AI agents to interact with VS Code:

create_diff

Creates and shows a diff for modifying existing files:

  • Shows changes preview before applying
  • Requires user approval
  • Only works with existing files

open_file

Opens files in the VS Code editor:

  • Used for viewing new or modified files

open_project

Opens a project folder in VS Code:

  • Sets up working directory for AI agent

check_extension_status

Checks if extension is installed and responding

get_extension_port

Gets the port number for VS Code MCP Extension

list_available_projects

Shows projects from port registry file

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Copyright 2025 Block, Inc.

This product includes software developed at Block, Inc.

FAQ

What is the VS Code MCP server?
VS Code is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for VS Code?
This profile displays 56 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.856 reviews
  • Aisha Singh· Dec 28, 2024

    According to our notes, VS Code benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Maya Garcia· Dec 16, 2024

    VS Code has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Kwame Jain· Dec 16, 2024

    VS Code is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Chen Torres· Dec 12, 2024

    VS Code is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Xiao Menon· Dec 12, 2024

    Useful MCP listing: VS Code is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Pratham Ware· Dec 4, 2024

    We evaluated VS Code against two servers with overlapping tools; this profile had the clearer scope statement.

  • Sakshi Patil· Nov 23, 2024

    Useful MCP listing: VS Code is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Kwame Harris· Nov 19, 2024

    I recommend VS Code for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Valentina Ghosh· Nov 15, 2024

    We wired VS Code into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Li Choi· Nov 7, 2024

    Strong directory entry: VS Code surfaces stars and publisher context so we could sanity-check maintenance before adopting.

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