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Overview

Raily supports the Model Context Protocol (MCP), enabling standardized communication between AI models and your content. MCP servers provide a consistent interface for AI systems to discover and access your data.

What is MCP?

Model Context Protocol is an open standard for AI-content interaction that:
  • Provides standardized content discovery
  • Enables structured data exchange
  • Supports authentication and authorization
  • Tracks usage and analytics

Standard Protocol

Industry-standard protocol supported by major AI providers

Easy Integration

Simple integration with AI applications and agents

Access Control

Built-in authentication and authorization

Analytics

Track how AI systems use your content

MCP Server Features

Content Discovery

Enable AI systems to discover your content through standardized MCP endpoints.

Authentication

Secure your MCP server with API keys or OAuth authentication methods.

Usage Policies

Control how content is used through MCP with policies for allowed purposes, rate limits, and quotas.

Metadata Exposure

Expose rich metadata about your content including titles, descriptions, topics, and licensing information.

Search Capabilities

Enable keyword, semantic, or hybrid search through your MCP server.

MCP Endpoints

Standard endpoints provided by Raily MCP servers:
  • Content discovery
  • Content access
  • Metadata query
  • Search

Best Practices

Clear Documentation

Provide clear documentation for AI systems using your MCP server

Rate Limiting

Set appropriate rate limits to protect your infrastructure

Monitoring

Monitor MCP usage for unusual patterns

Versioning

Version your MCP APIs for backward compatibility

Next Steps