Prompts

MCP prompts are reusable message templates that an MCP server exposes to a client. They help users start common AI workflows with consistent instructions and context. A prompt might prepare a code review, summarize an incident, analyze a customer account, or draft a project update. In MCP’s control model, prompts are user-controlled. The user explicitly chooses a prompt, often through a slash command, menu item, or command palette.

How MCP prompts work

A typical prompt flow is:

The client discovers prompts with prompts/list.
The user selects a prompt.
The client requests it with prompts/get and supplies any arguments.
The server returns one or more structured messages.
The client adds the messages to the AI interaction.

User         Client                         Server
 |             |---- prompts/list ----------->|
 |             |<--- available prompts --------|
 |-- selects ->|---- prompts/get + arguments ->|
 |             |<--- structured messages -------|

Servers declare the prompts capability during initialization when they support this feature.

What defines a prompt?

A prompt definition can include:

A unique programmatic name
An optional display title
A human-readable description
Optional arguments
Optional icons and metadata supported by the protocol version

{
  "name": "review_pull_request",
  "title": "Review pull request",
  "description": "Review a pull request for correctness, security, and maintainability.",
  "arguments": [
    {
      "name": "pull_request_url",
      "description": "The full URL of the pull request.",
      "required": true
    }
  ]
}

Arguments let one prompt template adapt to a specific repository, customer, date range, language, or other user-selected input.

What does `prompts/get` return?

The server returns a description and an ordered list of prompt messages. Each message has a user or assistant role and supported content.

{
  "description": "Review pull request 1042",
  "messages": [
    {
      "role": "user",
      "content": {
        "type": "text",
        "text": "Review this pull request. Identify correctness, security, and maintainability issues."
      }
    }
  ]
}

Prompt messages can contain text and other content types supported by the negotiated protocol version. They can also embed server-provided resources so the workflow arrives with relevant context.

Prompts, resources, and tools

MCP primitive	Main purpose	Typical controller
Prompt	Start a reusable AI workflow	User
Resource	Supply readable context	Application
Tool	Perform an operation	Model

A prompt can guide the model to use resources or tools, but it does not replace them. For example, a “Prepare account review” prompt can define the workflow. A customer resource can supply account context. A tool can retrieve current usage or create a follow-up task.

Examples of MCP prompts

Prompt	Arguments	Intended result
`review_pull_request`	Pull request URL	Structured code review
`summarize_incident`	Incident ID	Timeline and lessons learned
`prepare_customer_brief`	Customer ID	Account briefing
`explain_error`	Error message, language	Plain-English diagnosis
`draft_release_notes`	Version, audience	Release-note draft

Design prompts for clear selection

Use an action-oriented name and title.
Explain when the user should choose the prompt.
State the expected output.
Keep each argument focused and well described.
Validate required arguments before generating messages.
Keep instructions concise and specific.
Avoid silently adding unrelated goals.
Test prompts with missing, empty, and unusual inputs.

Prompt output should be treated as untrusted content. A prompt can influence model behavior, so clients and servers should avoid inserting secrets and should make the generated messages visible when appropriate.

Prompt updates

A server can declare listChanged support. If the available prompt list changes, it can send notifications/prompts/list_changed so the client can refresh its view. Clients should not assume every server or protocol version supports the same metadata or content types. They should follow negotiated capabilities.

Key takeaway

An MCP prompt is a user-selected, reusable template that returns structured messages for a consistent AI workflow.

Fundamentals

MCP Core Concepts

Build MCP Server

MCP Security

MCP Best Practices

How MCP prompts work

What defines a prompt?

What does `prompts/get` return?

Prompts, resources, and tools

Examples of MCP prompts

Design prompts for clear selection

Prompt updates

Key takeaway

​How MCP prompts work

​What defines a prompt?

​What does prompts/get return?

​Prompts, resources, and tools

​Examples of MCP prompts

​Design prompts for clear selection

​Prompt updates

​Key takeaway

How MCP prompts work

What defines a prompt?

What does `prompts/get` return?

Prompts, resources, and tools

Examples of MCP prompts

Design prompts for clear selection

Prompt updates

Key takeaway