Term
MCP
MCP — Model Context Protocol — is an open standard from Anthropic for connecting AI models to external data sources and tools through a unified interface.
MCP — explained in more detail
The Model Context Protocol is an open standard introduced by Anthropic to unify how external data sources and tools are wired into AI models. Instead of building a custom interface for every integration, MCP servers and MCP clients speak a shared protocol. Databases, APIs, file systems and issue trackers are exposed as tool servers.
Practical relevance
MCP servers are interchangeable across AI clients. A server that exposes access to an issue tracker, for example, can be used equally from Claude Desktop, Cursor or Claude Code. That lowers integration cost and shortens the path from “tool exists” to “tool is usable”.
Distinction from similar terms
MCP is not an AI model and not an agent — it is the underlying connectivity layer. Compared to a single vendor’s function-calling, MCP defines a cross-vendor interface: the same tool server works with different models and clients.
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GlossarEnsemble / Multi-Model Orchestration
Ensemble means combining several deliberately varied LLM runs or models whose findings complement each other. Multi-model orchestration drives these runs via orchestrators with sub-agents, so the union of results is larger than any single run.
LexikonFunction Calling / Tool Use
How an LLM uses tools: define a tool as a schema, the model picks the function and arguments, the result returns to the chat — the basis of every agent.