ihorponom/agentpack
by Various
Local task-state ledger for AI coding agents. Preserve decisions, source conclusions, evidence, and checkpoints across Codex, Claude Code, Cursor, and other MCP clients.
MCP
ihorponom/agentpack
Added 3 Sept 2026
Overview
A local task-state ledger for AI coding agents. It preserves decisions, source conclusions, evidence, and checkpoints across Codex, Claude Code, Cursor, and other MCP clients. Built in TypeScript, it runs as a developer tool to maintain continuity between sessions.
Best for
Best for
Developers juggling multiple AI coding agents who need persistent task context.
Use cases
- Track decisions and rationale across multiple AI coding sessions
- Store evidence and source conclusions for agent-driven changes
- Sync checkpoints between different MCP-compatible coding tools
How to use
Install
npm install -g agentpack-cli Tested with
Claude Desktop, Claude Code, Cursor, Continue
Notes
A local task-state ledger for AI coding agents. It preserves decisions, source conclusions, evidence, and checkpoints across Codex, Claude Code, Cursor, and other MCP clients. Built in TypeScript, it runs as a developer tool to maintain continuity between sessions.
17 stars on GitHub. Last updated 2026-08-29. Licensed MIT.
Use cases
- Track decisions and rationale across multiple AI coding sessions
- Store evidence and source conclusions for agent-driven changes
- Sync checkpoints between different MCP-compatible coding tools
Pros
- Local storage keeps task state private and offline
- Works across several popular AI coding clients via MCP
- Simple TypeScript codebase for easy customization
Cons
- Low star count suggests limited community validation
- Requires MCP client support, limiting adoption
- No built-in collaboration or remote sync features
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Local storage keeps task state private and offline
- Works across several popular AI coding clients via MCP
- Simple TypeScript codebase for easy customization
Cons
- Low star count suggests limited community validation
- Requires MCP client support, limiting adoption
- No built-in collaboration or remote sync features
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
Pairs with
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