Integration in Practice: Stack, Prompts and Use Cases
An MCP server exposes tools, resources and prompts from one system so any MCP-compatible AI client can use them over a standard protocol. A Model Context Protocol server is a small program that publishes three kinds of capability: tools (functions the model can call), resources (readable data the model can pull), and prompts (reusable templates). This guide pulls together everything on Onexial tagged integration — 8 connected nodes across definitions, workflows, tool stacks, comparisons, prompts and applied use cases — and orders it the way you would actually learn it: vocabulary first, then process, then tooling, then execution. Every item below links to a full node with its own examples and connections, so you can go as deep as you need without losing the map.
Core concepts behind Integration
Before wiring anything together, the vocabulary has to be precise. These 3 definitions cover the terms that show up in almost every Integration discussion — each one links to a full entry with an example and its own connections inside the graph.
MCP Server
An MCP server exposes tools, resources and prompts from one system so any MCP-compatible AI client can use them over a standard protocol.
MCP Client
An MCP client is the AI-side host that discovers servers, lists their tools and routes the model's calls to them.
MCP Transport (stdio vs Streamable HTTP)
MCP runs either as a local stdio process or as a remote streamable HTTP endpoint — the choice decides auth, deployment and who can reach it.
Workflows: how Integration runs end to end
Concepts only matter once they become a repeatable process. Below are 1 documented workflows that apply Integration to a concrete problem, with the steps, the tools involved and the variations worth testing.
The Integration tool stack
A stack is a set of tools chosen for one job, not a list of favourites. These 1 stacks show which combinations hold up in production for Integration, and what each layer is actually responsible for.
Trade-offs and comparisons
Most Integration decisions are trade-offs rather than right answers. These 1 comparisons break down the real differences, when each option wins, and the recommendation for the common case.
Prompts you can reuse
Prompts are reusable components. Each of these 1 prompts is written to be dropped into a Integration workflow with minimal editing, including the context it expects and an example output.
Real applications of Integration
Finally, 1 applied use cases: the situation, the system used to solve it, and the outcome. This is the layer that turns Integration from an idea into leverage.
Frequently asked questions
- What is MCP Server?
- A Model Context Protocol server is a small program that publishes three kinds of capability: tools (functions the model can call), resources (readable data the model can pull), and prompts (reusable templates). It speaks MCP over stdio or streamable HTTP, so the same server works with Claude, ChatGPT, Cursor, Codex or your own agent — no per-client integration code.
- What is an example of MCP Server?
- A CRM MCP server exposing `find_contact`, `create_deal` and `list_pipeline`, connected once and reused by three different AI clients.
- Why does MCP Server matter?
- An MCP server exposes tools, resources and prompts from one system so any MCP-compatible AI client can use them over a standard protocol.
- What should I learn after MCP Server?
- Open the related workflows and prompts further down this page: they show how this idea is applied in a real task, step by step.
- What is MCP Client?
- The client owns the connection lifecycle: it launches or dials servers, performs capability discovery, injects the tool schemas into the model's context, executes the calls the model requests, and returns results. Claude Desktop, Cursor, ChatGPT connectors and custom agents built with the AI SDK are all MCP clients.
- What is an example of MCP Client?
- Cursor as an MCP client connects to a Postgres server and a docs server, then lets the coding model query the schema while writing a migration.
- Why does MCP Client matter?
- An MCP client is the AI-side host that discovers servers, lists their tools and routes the model's calls to them.
- What should I learn after MCP Client?
- Open the related workflows and prompts further down this page: they show how this idea is applied in a real task, step by step.