What is MCP?
The Model Context Protocol is an open standard for connecting AI agents to external data and tools. Think of it as USB for LLMs: a single plug-and-play interface, regardless of which agent you use or which service you're connecting to.
Why a protocol exists
Every agent framework — Claude Desktop, Claude Code, OpenAI Agents, LangChain, your in-house stack — eventually needs the same thing: a way to let the model call a function, read a document, or fetch data from your service. Before MCP, every framework rolled its own glue. Result: every service had to build N integrations, one per framework.
MCP replaces those N integrations with one. A server speaks MCP; any client that speaks MCP can use it. No per-client adapters.
The three primitives
| Primitive | Owns | Best for |
|---|---|---|
| Tool | Server | Functions the agent calls — searches, side-effects, lookups |
| Resource | Server | Read-only documents the agent fetches by URI |
| Prompt | Server | Reusable prompt templates the agent can instantiate |
EDITED MCP's tools span competitive market data, trend research, and
messaging & promotions — some resolving fuzzy concepts into stable IDs, others
returning data directly — and a diagnostic resource
(mdmcp+data://session_id) is available too. Browse the live catalogue —
tools, resources, and any prompts — in the Reference, which is
generated from the server itself and always matches what's deployed.
For the deep dive on each, see:
- Concepts → Tools
- Concepts → Resources
- Concepts → Prompts
- The data — the entities EDITED resolves and their stable identifiers
How agents actually use MCP
The agent reads the tool catalogue once, decides which tool to call, and the server executes. The agent never has to know how the search backend works, what the schema is, or where the data lives — the tool description and input schema tell it everything.
How it differs from a REST API
| REST API | MCP | |
|---|---|---|
| Discovery | Out-of-band (OpenAPI doc) | Built-in (tools/list) |
| Calling | HTTP verb + URL | JSON-RPC method |
| Auth | Per-endpoint | Per-server |
| Streaming | Mixed (SSE, WebSockets, …) | Built into the transport |
| Audience | Humans + machines | Agents (designed for tool-use) |
You could wrap a REST API in an agent framework's tool layer. MCP formalizes the same idea, so the wrapper is the same everywhere.
This page is about MCP as a protocol. EDITED's MCP isn't a wrapper over its REST API, though: it's a distinct surface, designed with agent workflows in mind, with its own tools and normalized results — and for Trend & Research and Messaging & Promotions there's no REST API behind it at all. For which EDITED surface to reach for on a given job — MCP, the Query API, or the Jobs API — see MCP or the API?.
Going deeper
- The spec: modelcontextprotocol.io
- Why MCP for EDITED specifically: Recipes → Example workflow
- The security shape of EDITED's connector: Operations → Data privacy & security