Defined term
MCP (Model Context Protocol)
Open protocol for exposing tools, resources, and prompts to AI models in a standard way.
Model Context Protocol is a specification for how AI applications connect to data sources, tools, and prompts. It standardizes the interface so the same MCP server can be used by Claude, Cursor, or any compatible client. We use MCP servers in client engagements to expose proprietary tools without rewriting integration logic per model.
When it matters
When you need to expose enterprise tools and data to multiple AI clients (Claude, ChatGPT, internal agents) through a standard protocol. Avoids building bespoke integrations per AI client.
Real example
An MCP server exposing internal CRM (read), pricing engine (read), and ticket creation (write) to Claude Desktop for sales engineers. One server, three AI clients can connect, schema and auth managed centrally.
KPIs to watch
MCP server uptime (>99.9%), authentication failure rate (<0.1%), tool execution latency P95 (<2s).
Related terms
Tool use
An LLM's ability to call external functions, APIs, or services within a generation step.
Function calling
Specific implementation of tool use where the model emits structured JSON calls to registered functions.
Agentic AI
AI systems that can plan, take multi-step actions, and use tools to complete tasks autonomously.
Autonomous agent
An AI agent that completes a defined task without per-step human input.
See it in action
We use this every week
Book a 30-min call and we'll walk you through how MCP (Model Context Protocol) shows up in a real engagement we're running.
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