mpm

name	mpm
description	Access Claude MPM functionality and manage multi-agent orchestration
user-invocable	true
version	2.0.1
category	mpm-command
tags	["mpm-command","system","pm-required","framework"]
effort	medium

/mpm - Claude MPM Framework Guide

What is Claude MPM?

Claude MPM (Multi-Agent Project Manager) extends Claude Code with multi-agent orchestration, project-specific PM instructions, persistent agent memory, real-time monitoring via a WebSocket dashboard, and automation hooks. A PM agent coordinates specialized agents to complete work through structured delegation using the Task tool. MPM manages skills deployment, agent selection, session continuity, and cross-project messaging.

How Delegation Works

The PM receives user requests and delegates to specialized agents via the Task tool:

Task(description="[what to do]", subagent_type="[agent-type]")

• PM analyzes the request, breaks it into subtasks, and selects the right agent for each
• Each agent focuses on its specialty and returns results to PM
• Parallel execution when tasks are independent (e.g., frontend + backend simultaneously)
• Sequential execution when tasks depend on each other (e.g., implement, then test, then deploy)
• Agents should focus on their delegated task and return clear results -- PM handles orchestration
• If an agent needs help from another specialty, it reports back to PM rather than self-delegating

Typical workflow: Research -> Engineer -> Ops (deploy) -> Ops (verify) -> QA -> Documentation

Available Agents

Claude MPM deploys a diverse set of specialized agents for different types of work. The canonical, always-current agent list is available via:

• /agent-list skill: View all available agents
• Agent tool's available-agent-types: Check which agents are active in your environment
• Delegation guide: src/claude_mpm/agents/AGENT_DELEGATION.md

Representative Agent Categories

Core Agents (always deployed): engineer, research, qa, documentation, ops, security, ticketing

Extended Agents (deployed per project): version-control, data-engineer, product-owner, project-organizer, prompt-engineer, memory-manager

Language-Specific Engineers: python-engineer, typescript-engineer, javascript-engineer, golang-engineer, rust-engineer, java-engineer, ruby-engineer, php-engineer, dart-engineer

Framework Specialists: nextjs-engineer, react-engineer, svelte-engineer, tauri-engineer, phoenix-engineer

Platform Operations: local-ops, vercel-ops, gcp-ops, aws-ops, digitalocean-ops, clerk-ops

Quality & Testing: api-qa, web-qa, real-user, refactoring-engineer

Specialized: imagemagick, content, agentic-coder-optimizer, data-scientist

Note: The agent ecosystem evolves as features are added. Rather than listing every agent here (which would grow stale), use /agent-list or check your Agent tool's available-agent-types for the complete, current catalog.

Skills System

Skills are markdown files deployed to .claude/skills/{name}/SKILL.md that provide agents with specialized knowledge and procedures.

• User-invocable skills respond to /skill-name slash commands (e.g., /mpm, /mpm-help)
• Non-invocable skills activate automatically based on context triggers
• Skills have frontmatter with: name, description, user-invocable, version, category, tags
• Categories: mpm-command, pm-workflow, pm-reference, toolchains-*, universal-*
• Progressive disclosure: Metadata loads first; full content loads on trigger
• Skills can include references/ subdirectories for detailed supplementary content

Memory System

Agent memories provide persistent context across sessions.

• Storage: .claude-mpm/memories/{agent_id}_memories.md
• PM manages memory files directly (read, consolidate, save)
• Each agent has domain-specific memory categories
• Trigger phrases: "remember", "don't forget", "always", "never", "going forward"
• Size limit: 80KB per file (~20k tokens)
• Routing: Keyword-based routing sends memories to the appropriate agent
• Memories are automatically loaded when an agent is delegated work

Hooks and Dashboard

Claude Code hooks capture tool usage, responses, and agent activity in real-time.

Event flow: Hook -> Connection Manager -> Monitor Server -> Dashboard

Dashboard at http://localhost:8765/ shows:

• Tools being used and files being read/written
• Agent delegations and completions
• Session timeline and activity feed

Monitor commands: /mpm-monitor start, /mpm-monitor stop, /mpm-monitor status

Available Commands

Command	Description
/mpm	This guide -- MPM overview and framework reference
/mpm-help	Detailed help for MPM commands
/mpm-init	Initialize or update a project for MPM
/mpm-status	System health and status
/mpm-doctor	Run diagnostic checks
/mpm-config	Manage configuration
/mpm-monitor	Control monitoring server and dashboard
/mpm-version	Version information
/mpm-organize	Intelligent file consolidation
/mpm-ticket-view	Ticketing workflow management
/mpm-session-pause	Save session state for later
/mpm-session-resume	Resume from paused session
/mpm-postmortem	Analyze session errors

For Agents: How to Work Within MPM

When you receive a delegated task from PM:

1. Focus on your delegated task -- PM handles orchestration and coordination
2. Return clear results with evidence: file paths created/modified, test counts and pass rates, URLs, error details
3. Your agent memory is loaded automatically -- reference it for project-specific conventions and past decisions
4. If you need another specialty, report back to PM with what you need rather than self-delegating
5. Track files you create or modify -- PM will handle git operations and file tracking
6. Follow project patterns -- check your memory and existing code conventions before implementing
7. Escalate blockers immediately -- do not silently fail or produce partial results without explanation