VRChat MCP Server: Bridge Your Social VR Data into AI Workflows

Finally, a way to give your AI agents direct access to VRChat's social ecosystem. Instead of manually checking friend lists, searching for worlds, or managing avatars through VRChat's interface, this MCP server puts comprehensive VRChat functionality directly into your AI toolchain.

Why This Matters for Your Development Workflow

VRChat's API has always been powerful, but accessing it programmatically required writing custom integrations for every project. This MCP server standardizes that access, giving you instant VRChat capabilities in any MCP-compatible environment – starting with Claude Desktop, but extending to any tool that speaks MCP.

You get immediate access to friend management, avatar switching, world discovery, instance creation, and notification handling without writing a single line of VRChat API code.

What You Can Build With This

Community Management Automation: Have your AI assistant monitor group notifications, automatically respond to friend requests based on criteria you define, or manage VRChat community events by creating instances and sending invites.

Content Discovery Workflows: Search and curate VRChat worlds and avatars based on complex criteria. Your AI can find worlds matching specific themes, check instance availability, and even help you organize favorites into collections.

Social VR Analytics: Combine VRChat data with other tools to analyze social patterns, track world popularity, or monitor community engagement across your VRChat presence.

Avatar and World Management: Programmatically switch between avatars based on context, create private instances for meetings, or manage your VRChat presence as part of larger automation workflows.

Key Advantages

Zero VRChat API Boilerplate: Skip the authentication headaches, rate limiting logic, and endpoint mapping. The server handles VRChat's 2FA requirements, session management, and API quirks so you don't have to.

MCP Standardization: Every VRChat function follows MCP conventions, making it immediately compatible with your existing MCP toolchain and future-proofing your integrations.

Comprehensive Coverage: 15+ tools covering everything from basic friend management to advanced group operations and notification handling. You're not limited to a subset of VRChat's functionality.

Claude Desktop Ready: Drop the configuration into your Claude Desktop setup and start using VRChat data in conversations immediately. No separate server management needed.

Integration Setup

Getting this running in Claude Desktop takes under 2 minutes:

1. Get your VRChat auth token using the included helper: npx vrchat-auth-token-checker
2. Add the server config to your Claude Desktop settings
3. Start using VRChat tools in your conversations immediately

For programmatic use, it's just as straightforward:

export VRCHAT_USERNAME=your_username
export VRCHAT_AUTH_TOKEN=your_auth_token
npx vrchat-mcp

The server handles all the VRChat API complexity – authentication, rate limiting, error handling, and data formatting.

Real Implementation Examples

Automated Community Moderation: Your AI can monitor group notifications, check new member requests against criteria, and automatically handle routine community management tasks.

Event Coordination: Create private instances for meetings, send targeted invites to specific friend groups, and manage VRChat-based events as part of larger workflows.

Content Curation: Search worlds by tags or creators, organize discoveries into favorite collections, and track which content resonates with your community.

Social Analytics: Pull friend activity data, analyze world usage patterns, and generate insights about your VRChat social graph.

Why Choose This Over Direct API Integration

You could write direct VRChat API calls, but you'd spend weeks handling authentication flows, debugging rate limits, and maintaining API client code. This server gives you production-ready VRChat integration in minutes, with the added benefit of MCP standardization that makes it work seamlessly with your existing AI toolchain.

The TypeScript implementation is solid, well-documented, and actively maintained. The 37 stars and clean codebase indicate this isn't a weekend project – it's a reliable tool you can build on.

If you're working with social VR data or building AI agents that need to interact with VRChat, this MCP server belongs in your toolkit. It transforms VRChat from a manual interface into a programmable social platform for your AI workflows.