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a2cr/a2cr

by Various

MCP server for client-encrypted AI agent handoffs with WorkBaton and WorkStash

A

MCP

a2cr/a2cr

Added 1 June 2026

#agent-memory #ai #ai-agents #claude-code #codex #coding-agents #context-management #context-window

Overview

a2cr/a2cr is an MCP server that enables client-encrypted handoffs between AI agents using WorkBaton and WorkStash. It provides a standardized protocol for passing encrypted context and tasks between agents, ensuring data confidentiality during transfers.

Best for

Best for
Developers building multi-agent systems that need encrypted context handoffs

Use cases

  • Securely hand off a multi-step task from one AI agent to another
  • Store and retrieve encrypted agent state with WorkStash
  • Coordinate agent workflows where each agent receives only its authorized context

Notes

a2cr/a2cr is an MCP server that enables client-encrypted handoffs between AI agents using WorkBaton and WorkStash. It provides a standardized protocol for passing encrypted context and tasks between agents, ensuring data confidentiality during transfers.

0 stars on GitHub. Last updated 2026-06-01.

Use cases

  • Securely hand off a multi-step task from one AI agent to another
  • Store and retrieve encrypted agent state with WorkStash
  • Coordinate agent workflows where each agent receives only its authorized context

Pros

  • Client-side encryption keeps sensitive agent data private during handoffs
  • Standard MCP protocol makes integration with existing agent frameworks straightforward
  • Lightweight Python implementation with no external dependencies beyond MCP

Cons

  • Zero stars and no community adoption indicates early-stage or experimental project
  • Limited documentation and examples for real-world deployment
  • Requires both agents to support the same encryption and protocol version

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

Pros

  • Client-side encryption keeps sensitive agent data private during handoffs
  • Standard MCP protocol makes integration with existing agent frameworks straightforward
  • Lightweight Python implementation with no external dependencies beyond MCP

Cons

  • Zero stars and no community adoption indicates early-stage or experimental project
  • Limited documentation and examples for real-world deployment
  • Requires both agents to support the same encryption and protocol version
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