MCP
What Is the Model Context Protocol?
The Model Context Protocol (MCP) is an open standard that lets AI models connect to external tools and data sources. Think of it as a USB port for AI — a universal interface that any AI client can plug into to gain new capabilities.
When an AI model connects to an MCP server, it gains access to tools (functions it can call), resources (data it can read), and prompts (templates it can use). The model decides when and how to use these capabilities based on the conversation.
How OBTO Uses MCP
OBTO exposes its entire deployment platform as an MCP server. When you connect your AI client to your OBTO MCP endpoint, the AI model gains the ability to:
Create applications — Scaffold new full-stack projects
Deploy code — Write server scripts, routes, pages, stylesheets, and JavaScript modules directly to the platform
Read existing code — Fetch any artifact to understand or modify it
Search codebases — Semantic vector search across your entire app
Generate previews — Create live preview URLs for testing
Patch files — Surgically modify existing code without rewriting entire files
The AI doesn't need a terminal, a file system, or Git. It uses OBTO's MCP tools to deploy code the same way a human developer would use an IDE and a deploy script — except it does it in seconds, within the same conversation where you described what you wanted.
Your MCP Endpoint
Every OBTO user gets a personal MCP server URL. This URL is unique to your account and scoped to your environment (domain).
Format:
You receive this URL after signing in at obto.co. It's displayed on your landing page.
Connecting Your AI Client
Each AI client has a different way to add MCP servers. Here's the overview:
Claude Desktop
Open Settings → MCP Servers
Click Add Server
Paste your OBTO MCP endpoint URL
Claude will redirect you to authenticate via OAuth
Click Approve — OBTO's tools will appear in your available tools
Claude Web
Open or create a Project
In project settings, go to Integrations
Add your OBTO MCP server URL
Authorize when prompted
Cursor
Open Settings → MCP
Add a new server with your OBTO endpoint URL
The tools appear automatically after connection
VS Code (GitHub Copilot)
Add MCP server configuration to your
settings.jsonor.vscode/mcp.jsonSpecify the OBTO endpoint URL
Restart — tools are available through Copilot
OpenAI Codex
Add your OBTO MCP endpoint URL in the agent configuration
Tools are available once connected
For detailed per-client setup guides, see the dedicated pages: Claude, Codex, AntiGravity, VSCode, Cursor IDE.
The OBTO Skill File
Connecting the MCP server gives the AI access to tools. But for the AI to use those tools correctly, it needs context — deployment order, platform conventions, collection types, the xe. pattern, and more.
That's what the OBTO Skill file (SKILL.md) provides. It's a set of instructions that teaches AI models how to build applications on OBTO.
Download it from GitHub: github.com/obto-inc/platform
Place the skill file where your AI client can access it:
Claude Desktop
Add to project knowledge or attach as a file
Claude Web
Upload as a file attachment
Cursor
Place in workspace root or .cursor/skills/
VS Code
Place in workspace root
AntiGravity
Place in .agent/skills/ directory
Why is this separate from the MCP server? MCP defines what tools are available. The Skill file teaches the AI when and how to use them. This separation means you can upgrade the skill instructions independently of the platform's tooling.
Authentication Flow
OBTO uses OAuth 2.0 for MCP authentication:
Your AI client sends a connection request to your MCP endpoint
OBTO redirects to Google OAuth for authentication
You approve the connection
The AI client receives a token scoped to your domain
All subsequent tool calls are authenticated automatically
Your token is scoped to your OBTO domain — the AI can only access applications and data within your environment.
Next Steps
MCP Tools - OOB — See every tool available out of the box
Create Tool — Build custom MCP tools for your specific workflows
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