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by jarmstrong158 Β· Python

Knowledge-lifecycle MCP: turn agent work into memory, recall it across projects, promote to org.

Knowledge-lifecycle MCP: turn agent work into memory, recall it across projects, promote to org.

πŸ› οΈ Key Features

  • Grounded in Model Context Protocol (MCP) server operations for knowledge lifecycles
  • Bridges agentsync events (claims, finishes, notes, changed files) with context-keeper decisions and constraints
  • Adds distill() capability to convert events into organization-wide memory

πŸš€ Use Cases

  • Capture and consolidate agent work across projects
  • Promote actionable knowledge to the organizational memory layer
  • Recall and surface prior decisions and constraints during new agent runs

⚑ Developer Benefits

  • Clear MCP server implementation for knowledge lifecycle workflows
  • Facilitates cross-project memory retention and retrieval
  • Aligns agent activity with organizational context and constraints

⚠️ Limitations

  • Based on excerpted readme; full behavior depends on integration with agentsync and context-keeper components

Topics

ai-agentsclaudeknowledge-managementmcpmcp-servermemorymodel-context-protocol
Cambium - agentage MCP Catalog