# Agentshandbook Handbook MCP server

Source: https://glimind.com/server/mcp-registry%2Fcom.agentshandbook%2Fhandbook
Registry id: `mcp-registry/com.agentshandbook/handbook`
Status: live (checked 2026-10-27T01:44:28.604Z)

## Measurements (30 days)

- Uptime: 100%
- Checks: 2860
- Outages (90 days): 0

## Install

```json
{
  "mcpServers": {
    "agentshandbook-handbook-mcp-server": {
      "type": "http",
      "url": "https://agentshandbook.com/mcp"
    }
  }
}
```

Claude Code:

```sh
claude mcp add --transport http agentshandbook-handbook-mcp-server https://agentshandbook.com/mcp
```

## Tools (11)

- `check_submission`: Returns the review status of an Agents Handbook submission (pending, reviewed, approved, rejected or published) with the review agent's reasons.
- `get_agent`: Returns an agent profile from the Agents Handbook: what the agent is good at, its limits, how it connects to tools, and the playbooks and lessons written for it
- `get_lessons`: Returns known failure modes and their fixes from the Agents Handbook, filtered by agent, playbook, lesson slug or a plain-words description of the problem.
- `get_playbook`: Returns one Agents Handbook playbook as markdown: summary, human checkpoints, the prompt (the variant written for the given agent, if provided), steps with chec
- `list_tasks`: Lists the jobs the Agents Handbook covers, grouped by category, with the agents that have playbooks for each job.
- `register_contributor`: Creates an Agents Handbook contributor key for a public handle, so run reports and submissions sent with it (Authorization: Bearer <key>) are credited and get h
- `report_run`: Records the outcome of running an Agents Handbook playbook (worked, worked with changes, or failed), with what changed and an optional lesson. Reports enter a r
- `search_playbooks`: Searches the Agents Handbook for playbooks that match a real-world job done with an AI agent, described in plain words (for example 'cancel subscriptions from e
- `submit_playbook`: Sends a full playbook for a job completed with an AI agent into the Agents Handbook review queue: title, agents used, summary, the prompt that worked (with [pla
- `submit_use_case`: Sends a short use case (a job done with an agent that has no playbook yet), a lesson, or a correction to an existing playbook into the Agents Handbook review qu
- `whats_new`: Lists the most recently updated playbooks and the latest community run reports in the Agents Handbook.

Measured by Glimind (https://glimind.com): MCP handshake + tool list only, no tool is ever called. CC BY 4.0.