/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:

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