# handoff-mcp

> Use this tool when you need to enable seamless collaboration between different AI agents on a project, persisting and sharing context to prevent knowledge loss and improve overall efficiency. The handoff-mcp hub accepts project context as input and provides a shared memory output, allowing LLMs to pick up where others left off. Ideal for use cases requiring multi-agent workflows, such as complex task automation and large-scale data processing.

Canonical page: https://skillsregistry.net/skills/juan-severiano-handoff-mcp  
JSON: https://api.skillsregistry.net/v1/skills/juan-severiano-handoff-mcp

## Description

Shared memory hub for LLMs to persist and share project context, enabling seamless handoffs between different AI agents.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-05-17

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/o42ea623tj)
- **Repository:** <https://github.com/Juan-Severiano/handoff-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "juan-severiano-handoff-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/juan-severiano-handoff-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/juan-severiano-handoff-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt