Model Context Protocol (MCP) Hub.
The universal standard for connecting AI agents to enterprise tools. Discover how MCP securely bridges the gap between foundation models and your private data.
Interactive MCP Quick-Starter
Connect your AI assistant to Memora's persistent memory layer. Runs locally over stdio.
{
"mcpServers": {
"memora-memory": {
"command": "npx",
"args": [
"-y",
"@memora/mcp-server@latest"
],
"env": {
"MEMORA_API_KEY": "YOUR_MEMORA_API_KEY",
"MEMORA_WORKSPACE_ID": "ws_enterprise_main"
}
}
}
}Deep-dive modules & architecture chapters.
Select a topic below to explore implementation details, technical benchmarks, and security architectures.
How MCP Servers Work: Resources, Prompts, and Tools
A deep dive into the three core primitives of the Model Context Protocol architecture and how servers expose local context to AI clients.
Read ChapterMCP for AI Agents: Enabling Autonomous Workflows
How autonomous AI Agents utilize the Model Context Protocol to execute actions securely across disparate enterprise systems without custom glue code.
Read ChapterMCP Security Architecture: Secure AI Integration for Enterprises
How the Model Context Protocol (MCP) shapes enterprise AI security: local vs remote servers, transport choices, server-side access control, and risks like prompt injection and tool poisoning.
Read ChapterMCP vs. REST APIs for AI Integration
Why standard REST APIs are insufficient for Agentic AI, and why the Model Context Protocol provides the necessary discovery mechanisms for zero-shot integration.
Read ChapterWhat is the Model Context Protocol (MCP)?
A comprehensive overview of the Model Context Protocol, why it was created, and how it standardizes AI integration for enterprise systems.
Read ChapterPut Model Context Protocol (MCP) to work for your team.
Start free, connect your first tool and ask your first question today.