Use this tool to retrieve the full summary and performance analysis for a completed sprint. The summary includes scope management analysis, velocity and task completion metrics, workload distribution per team member, task type breakdown, and AI-generated retrospective recommendations. Use this tool to drive sprint retrospectives, track team velocity over time, or surface improvement areas after a sprint closes.

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The sprint must be completed and must have been created after January 1, 2025. Calling this tool on a planned or active sprint, or on a sprint that predates 2025, will return an error. The sprint board must also have the sprint_summary column configured.

Use get_sprints_metadata to find completed sprint IDs before calling this tool. When viewing the "Completed by Assignee" section of the summary, user IDs appear in the format @user-12345678. Use list_users_and_teams with the numeric user ID (the 8 digits after @user-) and includeTeams: false to resolve them to names.

Parameters

Example

Retrieve the summary for sprint ID 11545180130 (Sprint 34):

{
  "sprintId": 11545180130
}

The summary includes sections for:

• Scope Management — planned vs. unplanned tasks, scope creep analysis
• Velocity & Performance — individual velocity, task completion rates, workload distribution per team member
• Task Distribution — breakdown of completed tasks by type (Feature, Bug, Tech Debt, Infrastructure, etc.)
• AI Recommendations — action items, process improvements, and retrospective focus areas

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If the sprint board doesn't have the sprint_summary column configured, the tool returns a validation error: "Sprint item is missing required columns: sprint_summary". This column is part of the monday Dev sprint board setup and must be present for this tool to work.

Programmatic equivalent

Sprint summaries are stored as monday.com items. You can retrieve the raw item data using the GraphQL API:

query {
  items(ids: [11545180130]) {
    id
    name
    column_values {
      id
      text
      value
    }
  }
}

The MCP tool interprets the sprint_summary column value and structures it into the sections described above. For raw column data, use the items query directly. See the Items Page reference for full documentation.