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pasichDev/docket

by Various

Local-first, self-hostable coordination workspace for AI coding agents. Shared tasks, claims, sync and MCP integration.

MCP

pasichDev/docket

Added 23 Sept 2026

#ai-agent #backlog #claude #claude-code #claude-desktop #mcp #mcp-server #model-context-protocol

Overview

Local-first, self-hostable coordination workspace for AI coding agents. It provides shared tasks, claims, sync, and MCP integration so multiple agents can coordinate work without relying on a cloud service.

Best for

Best for
Developers piloting multi-agent workflows who want a self-hosted coordination layer.

Use cases

  • Coordinate multiple AI coding agents on shared task lists
  • Claim tasks to prevent duplicate work across agents
  • Integrate agent workflows via MCP for task sync

How to use

Install

npx -y @pasichdev/docket setup

Tested with

Claude Desktop, Claude Code, Cursor, Windsurf

Notes

Local-first, self-hostable coordination workspace for AI coding agents. It provides shared tasks, claims, sync, and MCP integration so multiple agents can coordinate work without relying on a cloud service.

9 stars on GitHub. Last updated 2026-09-22. Licensed MIT.

Use cases

  • Coordinate multiple AI coding agents on shared task lists
  • Claim tasks to prevent duplicate work across agents
  • Integrate agent workflows via MCP for task sync

Pros

  • Local-first and self-hostable, keeping data on your own infrastructure
  • MCP integration allows direct agent connectivity
  • Focused on a concrete coordination problem for agent teams

Cons

  • Very early-stage project with only 9 stars, so maturity is unproven
  • Small community and likely limited documentation or support
  • Narrow feature set centered on tasks and claims, not broader project management

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

Pros

  • Local-first and self-hostable, keeping data on your own infrastructure
  • MCP integration allows direct agent connectivity
  • Focused on a concrete coordination problem for agent teams

Cons

  • Very early-stage project with only 9 stars, so maturity is unproven
  • Small community and likely limited documentation or support
  • Narrow feature set centered on tasks and claims, not broader project management
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