MCP (Model Context Protocol)
An open protocol for exposing tools, data sources, and prompts to AI agents in a standard way.
What is MCP (Model Context Protocol)?
MCP lets you wrap an internal API or a third-party agent platform as a tool any compatible agent can invoke. In practice it is the integration glue between platforms — for example, running n8n or CrewAI flows as tools inside a VDF AI Network. See Model Context Protocol and Integrate n8n & CrewAI as MCP Tools.
Why it matters for on-premise & regulated AI
MCP standardises how agents reach tools and data — which makes it the natural enforcement point for on-prem governance. Self-hosting your MCP servers means connectors to Jira, databases, and file stores run inside your network with your credentials, and every tool invocation can be policy-checked and logged locally. The alternative — cloud-hosted connectors holding standing credentials to internal systems — is precisely what security teams reject.
Read the full guide: MCP (Model Context Protocol) — in-depth article →
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Putting MCP (Model Context Protocol) to work?
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