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dkships/pm-copilot

by Various

MCP server that triangulates customer support tickets and feature requests to help PMs decide what to build next

D

MCP

dkships/pm-copilot

Added 1 June 2026

#ai-tools #claude #customer-feedback #helpscout #mcp #mcp-server #product-management #productlift

Overview

dkships/pm-copilot is an MCP server that aggregates customer support tickets and feature requests. It triangulates these data sources to help product managers decide which features to build next.

Best for

Best for
Product managers seeking a lightweight, open source tool to aggregate customer feedback and prioritize features

Use cases

  • Prioritize feature development based on aggregated customer feedback
  • Identify recurring issues from support tickets to inform roadmap decisions
  • Bridge data from support and feature requests for product planning

Notes

dkships/pm-copilot is an MCP server that aggregates customer support tickets and feature requests. It triangulates these data sources to help product managers decide which features to build next.

26 stars on GitHub. Last updated 2026-06-01. Licensed MIT.

Use cases

  • Prioritize feature development based on aggregated customer feedback
  • Identify recurring issues from support tickets to inform roadmap decisions
  • Bridge data from support and feature requests for product planning

Pros

  • Open source and free to use
  • Lightweight MCP server integration
  • Directly addresses common PM pain point of decision-making from feedback

Cons

  • Low GitHub stars (26) indicating limited community traction
  • Requires existing ticket and feature request sources to function
  • Depends on data quality and completeness for useful output

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Open source and free to use
  • Lightweight MCP server integration
  • Directly addresses common PM pain point of decision-making from feedback

Cons

  • Low GitHub stars (26) indicating limited community traction
  • Requires existing ticket and feature request sources to function
  • Depends on data quality and completeness for useful output

Pairs with

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