Model Context Protocol (MCP) is a standard that enables applications to provide context to large language models (LLMs). With MCP servers, AI assistants can retrieve additional information relevant to a user's query.
Realm provides built-in MCP server capabilities that expose your API Docs to AI assistants.
- Real-time API guidance — users receive accurate, contextual help about API endpoints and operations.
- Secure API access — AI assistants can make authenticated requests to act on behalf of a user.
- Dynamic documentation — AI assistants can extract and explain API reference content based on user needs.
Use the Docs MCP server to explore and discover APIs in your project. The server provides tools for browsing API definitions, exploring endpoints, and understanding API schemas.
- Browse available APIs and their definitions.
- Explore API endpoints and operations.
- Access schema definitions and data models.
- Navigate API paths and their details.
After adding the option to the config file, the Docs is registered at your root URL under the /mcp
path. For example: https://example.com/mcp
.
If your project requires login (rbac
or requiresLogin
configured), Docs MCP Server requires the user to authenticate using the configured method. This requirement ensures that AI Agents can only access APIs and operations the authenticated user has permission to view.
Tool | Parameters | Description |
---|---|---|
whoami | - | Returns information about the authenticated user. |
Tool | Parameters | Description |
---|---|---|
list-apis | name?: string | Lists available APIs with their context and purpose. |
get-endpoints | name: string | Returns all endpoints and their descriptions for a specific API. |
get-endpoint-info | name: string path: string method: string | Returns comprehensive information about a specific endpoint, including parameters, security, and examples. |
get-security-schemes | name: string path: string method: string | Gets the security schemes for a specific API. |
get-full-spec-document | name: string | Returns the complete OpenAPI definition for an API. |
Tool | Parameters | Description |
---|---|---|
search | query: string | Searches documentation and returns relevant content for a query. |
The Docs MCP server is registered at your root URL under the /mcp
path.
Users can connect their preferred AI tools that support MCP (for example, Cursor, Claude Code and VS Code) to your MCP server.
- Enable the MCP server in your configuration.
- Copy your MCP server URL and add it to your tool.
After connecting, the tool can access your OpenAPI documentation.
- In Cursor, open the command palette.
- macOS:
Command + Shift + P
- Windows/Linux:
Ctrl + Shift + P
- macOS:
- Type "Open MCP settings" in the command palette.
- Select "Add custom MCP".
Cursor opens the mcp.json
file.
- In
mcp.json
, add your server configuration:
{
"mcpServers": {
"example-mcp": {
"url": "https://example.com/mcp"
}
}
}
Optionally, you can also pass additional headers that will be sent with each request:
{
"mcpServers": {
"example-mcp": {
"url": "https://example.com/mcp",
"headers": {
"Authorization": "Basic MTIzOjEyMw=="
}
}
}
}
Save the
mcp.json
file.Return to MCP settings and confirm the connection. If authentication is required, select Needs login and complete the sign‑in flow. After connecting, Cursor displays the list of available tools.
In Cursor chat (Agent mode), ask a question that triggers an MCP tool.
- MCP configuration reference - Configure MCP for your project