Model Context Protocol

Integrations connect your app to a service. MCP connects the agent to one instead. The Model Context Protocol is an open standard for giving an AI agent extra tools and data to work with as it builds your app.

What MCP Adds

An MCP server exposes a set of tools and, sometimes, data the agent can use while it builds your app. Where an OAuth connection lets the finished app act with a service, MCP works one level up: it expands what the agent can do while it's working on your behalf.

That's useful when you want the agent to:

• Read live documentation or references for a library or API as it writes code.
• Query a system or database to inform what it builds.
• Reach a specialized capability that a particular MCP server provides.

Add an MCP Server

1. From My Project, open the More… menu and click MCP Servers. Alternatively, right-click the project or click in the Agent Chat to find this option.
2. Add the MCP Server entry under mcpServers, keyed by a server name, with the details that server needs.
3. Click Save to write the config file.
4. With the server added, the agent can call its tools while it works on your project. Describe what you want, and the agent reaches for the new tools when they help.

Configure a Server

Each entry under mcpServers defines how its server is reached. Its type must be stdio, sse, or http:

• A server name as the key, so you can recognize it in the config.
• A stdio server is local: it declares a command to run, with optional args, env, and cwd.
• An sse or http server is remote: it declares a url (http or https) and may include headers, such as an authorization token.

Check the server's own documentation for the exact values it expects. The configuration is stored with the project in .mcp.json, so it stays with the app rather than needing set up again each time.

Use It in a Prompt

The agent calls a tool when your prompt makes it the obvious way to get something done. To make that more likely:

• Name the source in your prompt: "Use the records from my database MCP server to seed the list" is clearer than hoping the agent reaches for it.
• Describe the goal, not the mechanics: Say what you want built; let the agent decide which tool fits.
• Check the result: If the agent didn't use a connected tool, say so and point it at the server explicitly.

Expose Your App as an MCP Server

Everything above connects the agent to an outside MCP server. The /create-mcp-server command runs the other direction: it turns your app into an MCP server that other AI tools can connect to, exposing your app's own data and actions as tools.

Type /create-mcp-server in the Agent Chat composer. You can add free-text preferences after it, such as /create-mcp-server read-only tools, to shape what the server exposes.

The agent then scaffolds a server around your app's own data and actions:

• A stdio server by default: a local script that reads your app's data directory at runtime and exposes tools shaped around what your app stores. It works even while your app is closed.
• An http server on request: an in-app server bound to localhost, for cases that need your app's live, in-memory state rather than just its stored data. It works only while your app is running.

Before finishing, the agent runs a self-test, then gives you copy-paste install commands for Claude Code, Codex CLI, Cursor, or Claude Desktop.

MCP vs OAuth

MCP and an OAuth integration solve different problems, and an app can use both. An OAuth integration connects your finished app to a service so the running app can act as you, reading and writing that service's data on your behalf. MCP works one level up: it connects the agent to extra tools and data while it builds, expanding what the agent itself can do as it writes your app. In short, OAuth extends your app's reach; MCP extends the agent's.