Works with the AI Agents you already use
Handoff-MCP
Durable session memory and project-scoped TODO management for AI agents via MCP.
Free
Handoff-MCP
Example session with this skill installed
I'm done for the day. Can you save a handoff for the auth refactor? I finished the JWT logic in auth.ts but still need to update the middleware.
- Read your context and instructions
- Compiled the handoff-mcp
I have recorded the current state of the auth refactor and updated the project TODO list. The handoff includes the completed JWT logic and specific instructions for the middleware updates.
Project Handoff: Auth Refactor
| Item | Type | Status | Details |
|---|---|---|---|
| JWT Implementation | Task | Completed | Logic implemented in src/lib/auth.ts. |
| Middleware Update | Task | Pending | Need to integrate new JWT verification in src/middleware.ts. |
| Session State | Handoff | Active | Refactor is 50% complete. Auth service is stable but not hooked to routes. |
| Context Compact | Summary | Saved | Compacted current discussion on token expiration into the handoff store. |
Next steps
- Run
handoff_listwhen you return to see the full implementation details. - Execute
todo_updatefor the middleware task once the route protection is verified. - Review the
auth.tsexports to ensure they match the middleware requirements.
Connects securely to your tools. The creator never sees your data.
About this skill
LLM context windows reset every session, causing agents to lose track of progress, pending tasks, and architectural decisions. This skill provides a durable memory layer for your agent using a project-local MCP server to ensure continuity between sessions.
What it does
- Persistent TODO tracking manages concrete tasks with priorities, tags, and status updates directly in the project scope.
- Session handoffs record the current state, key decisions, and specific file paths at the end of a work interval.
- Context management generates reports on active context and compacts bloated sessions into digestible summaries.
- Durable storage keeps all breadcrumbs and tasks in a local store independent of the conversation history.
How it works
- Use
handoff_listandtodo_listat the start of a new session to restore project state. - Add new tasks via
todo_addas requirements emerge during development. - Call
context_reportwhen the prompt window feels cluttered to identify what to prune. - Execute
handoff_addbefore closing the session to leave instructions for the next agent instance.
Frameworks & tools
This skill requires the Handoff MCP server. It is designed for use with Model Context Protocol compatible environments like Claude Desktop, Cursor, or specialized IDE agents.
Why this beats prompting it yourself
Relying on chat history for project state leads to hallucinations as the context window fills up. This skill moves project tracking into a structured local database that persists even if you clear your chat or switch models.
Use cases
- Resuming a complex refactoring job after a break without re-explaining the plan.
- Coordinating between multiple specialized agents by leaving breadcrumbs in a shared store.
- Managing long-running project roadmaps directly within the developer environment.
Known limitations
Requires a running Handoff MCP server. Storage is repository-scoped and does not synchronize across different machines unless the local store is shared.
What's included (3 skills)
handoff-mcp
Use the Handoff MCP server for durable, project-scoped TODOs and session handoffs across agent sessions; apply when work needs breadcrumbs, next steps, or context-reduction guidance.
handoff-mcp
Use the Handoff MCP server for durable, project-scoped TODOs and session handoffs across agent sessions; apply when work needs breadcrumbs, next steps, or context-reduction guidance.
handoff-mcp
Use the Handoff MCP server for durable, project-scoped TODOs and session handoffs across agent sessions; apply when work needs breadcrumbs, next steps, or context-reduction guidance.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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