VS Code▌
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.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
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
- Install the MCP Server
npx vscode-mcp-server install
- Install the MCP Extension
Configuration
Goose Desktop Setup

- 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.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 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
4.8★★★★★56 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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