MCP Server
The value of MCP is on the server side: one wrapper around Jira, Datadog, or your internal API.
The server is a power adapter. Your service has a weird plug. MCP is the standard outlet every client already knows.
Visual Workflows
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Overview
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One tool call
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The LLM never talks to Jira directly. It talks to the MCP server.
Key Takeaways
- 1.A server wraps a real system and speaks MCP to any client.
- 2.It advertises tools with name, description, and JSON Schema.
- 3.call_tool runs your code and returns text (or images) as content.
- 4.Write the server once — Cursor and your agent both consume it.
- 5.Keep tool descriptions honest — the LLM chooses tools from those sentences.
Learn elsewhere
- →Full build steps — Build MCP Server
- →Resources vs tools — next two modules
Real Example
Scenario
A Jira server exposes create_ticket, search_issues, and add_comment. Cursor and a support agent both use it without knowing Jira's REST shape.
What you would do
In Model Context Protocol, apply MCP Server to this scenario: A Jira server exposes create_ticket, search_issues, and add_comment. Identify the inputs, run the technique, validate the output, and note one thing you would monitor in production.
Commands
Commands to Remember
list_tools advertises JSON Schemacall_tool runs your functionReturn TextContent, do not print to stdoutstdio servers must keep stdout clean for JSON-RPC
Cheat Sheet
Quick recap
quick ref- •Server = wrapper + MCP handlers
- •name + description + inputSchema
- •call_tool returns content, not prints
- •Descriptions are how the LLM picks tools
Common Mistakes
- ✕Printing debug logs to stdout on a stdio server
- ✕Vague tool descriptions so the LLM picks the wrong tool
- ✕Crashing the process instead of returning a tool error