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Monomind - Enterprise AI agent orchestration for Claude Code. Deploy 60+ specialized agents in coordinated swarms with self-learning, fault-tolerant consensus, vector memory, and MCP integration

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    Readme

    Monomind

    Monomind

    Hire an AI team. Set a goal. Walk away.
    Autonomous Claude Code orchestration with persistent memory, self-coordinating agent orgs, and a codebase knowledge graph.

    Docs npm downloads stars license node

    🏒 Orgs  Β·  πŸš€ Quickstart  Β·  ⚑ Mastermind  Β·  πŸ“‹ Commands  Β·  πŸ—οΈ Architecture


    What is Monomind?

    Claude Code is already powerful. Monomind makes it run itself.

    Install once. Wire it into Claude Code. Then instead of prompting Claude to do individual tasks, you tell Monomind what outcome you want β€” and it assembles a team, coordinates the work, and delivers.

    # Assemble an AI content team and let it run
    /mastermind:createorg content-team "publish 3 SEO-optimized posts per week"
    /mastermind:runorg --org content-team
    
    # Or run the autonomous code improvement loop
    /mastermind:autodev --tillend --focus security

    That's it. Come back later.


    🏒 Autonomous Organizations

    This is the headline feature. Build a persistent AI organization β€” roles, hierarchy, shared task board β€” and start it as a background daemon that runs without you.

    The idea

    Every business function needs a team. Monomind lets you design that team in one command, then run it forever. The org persists across sessions. It checkpoints, recovers from failures, and coordinates its agents through a shared task board β€” all automatically.

    flowchart TD
        U(["You"])
        CO["/mastermind:createorg\nDefine goal + roles"]
        RO["/mastermind:runorg\nStart daemon"]
        BOSS["Boss Agent\ncoordinator"]
        W["Writer\nContent Creator"]
        S["SEO Specialist"]
        R["Reviewer"]
        M["Growth Marketer"]
        BOARD[("Shared\nTask Board")]
        MEM[("AgentDB\nMemory")]
    
        U --> CO --> RO --> BOSS
        BOSS -->|spawns| W
        BOSS -->|spawns| S
        BOSS -->|spawns| R
        BOSS -->|spawns| M
        BOSS <-->|claims + reports| BOARD
        W <-->|stores output| MEM
        S <-->|reads context| MEM
    
        style BOSS fill:#00D2AA22,stroke:#00D2AA
        style BOARD fill:#F59E0B22,stroke:#F59E0B
        style MEM fill:#8B5CF622,stroke:#8B5CF6

    Two commands to a running org

    Step 1 β€” Design it:

    / mastermind:createorg content-team
      "Build and publish 3 blog posts per week on AI dev tools"
    
    Deriving roles from goal...
    
    β•” ORG: content-team
    β•‘ TOPOLOGY: star (5 roles)
    
      boss      β†’ coordinator
      writer    β†’ Content Creator
      reviewer  β†’ reviewer
      marketer  β†’ Growth Hacker
      seo       β†’ SEO Specialist
    
    Type "go" to save, or describe changes.
    β†’ go
    
    βœ“ Saved .monomind/orgs/content-team.json
      β†’ Run: /mastermind:runorg --org content-team

    Step 2 β€” Start it:

    /mastermind:runorg --org content-team
    
    # Boss agent spawns in background
    # Coordinates all roles via shared task board
    # Checkpoints every 30 minutes
    # Loops until you stop it

    What runs under the hood

    What How
    Boss agent Coordinator type, no supervisor β€” owns the goal
    Role agents Spawned on demand, specialized by task type
    Task board Todo β†’ Doing β†’ Done, shared across all agents
    Memory All output stored in org-scoped AgentDB namespace
    Checkpoint State saved every 30 min β€” survives crashes and restarts
    Governance auto (free), board (approve sensitive), strict (approve all external actions)

    Topology is auto-derived

    graph LR
        A["1-3 roles"] -->|mesh| B["All-to-all\ndirect comms"]
        C["4-6 roles"] -->|star| D["Boss to workers\nfan-out"]
        E["7+ roles"] -->|hierarchical| F["Boss to leads to workers\nmiddle management"]

    Pre-built org types

    Org Goal Roles
    content-team 3 posts/week on AI tools Director Β· Writer Β· Reviewer Β· SEO Β· Growth
    dev-squad Features from design spec Lead Β· Architect Β· Developer Β· QA
    research-lab Weekly competitive intelligence Director Β· Researcher Β· Analyst Β· Writer
    sales-engine ICP research + outreach sequences Director Β· Outbound Β· Email Β· Researcher
    ops-squad 24/7 monitoring + incident response SRE Β· Security Β· Perf Β· Incident Cmdr

    Org management commands

    /mastermind:createorg <name> "<goal>"   # design org from a goal
    /mastermind:runorg --org <name>         # start as background daemon
    /mastermind:orgs                        # list all orgs + status
    /mastermind:orgstatus --org <name>      # detailed status for one org
    /mastermind:stoporg --org <name>        # stop a running org
    /mastermind:approve                     # review pending approval requests

    ⚑ The Autonomous Build Loop

    For code, /mastermind:autodev is the equivalent of Orgs β€” a loop that researches, builds, and reviews your codebase without stopping.

    flowchart LR
        R["Research\nParallel scan:\ngit log, files\nTODOs, graph\nmemory"] --> S
        S["Select\nFeasibility x\nblast-radius x\nfocus"] --> B
        B["Build\nArchitect\nCoder\nTester\nReviewer"] --> V
        V["Review Loop\nCode + Security\n+ Reality\nmax 5 iterations"] --> L
        L["Log + Loop\nStore to memory\n--tillend:\nschedule next"]
        L -->|"more to do"| R
    
        style R fill:#00D2AA22,stroke:#00D2AA
        style B fill:#8B5CF622,stroke:#8B5CF6
        style V fill:#F59E0B22,stroke:#F59E0B
        style L fill:#10B98122,stroke:#10B981
    /mastermind:autodev --tillend              # loop until nothing left
    /mastermind:autodev --tillend --focus security   # bias toward security fixes
    /mastermind:autodev 3                     # exactly 3 improvements

    Universal loop flags

    Flag Purpose
    --tillend Repeat until empty round (zero findings, zero actions)
    --repeat <N> Repeat exactly N times
    --focus <area> Bias toward: security Β· dx Β· performance
    --auto No confirmation prompts
    --maxruns <N> Safety cap (default 50)

    πŸš€ Quickstart

    # 1. Install
    npm install -g monomind
    
    # 2. Initialize in your project
    cd your-project
    monomind init
    
    # 3. Wire into Claude Code as an MCP server
    claude mcp add monomind npx monomind mcp start
    
    # 4. Start the background daemon
    monomind daemon start
    
    # 5. Health check
    monomind doctor --fix

    Open Claude Code. You now have 80+ slash commands available:

    /mastermind:autodev --tillend     # start autonomous code loop
    /mastermind:createorg my-team     # create your first AI org
    /mastermind:help                  # show all commands

    🧠 Memory That Persists

    Every session, every agent, every org writes to AgentDB β€” a hybrid SQLite + HNSW vector store that survives across sessions. The next time you run anything, Monomind already knows what was built, what failed, and which patterns work.

    graph TD
        L0["L0 - In-flight\nCurrent session drawers\nephemeral"]
        L1["L1 - Working\nCross-session memory\nBM25 K1=1.5, B=0.75"]
        L2["L2 - Long-term\nAgentDB + HNSW index\nSemantic search"]
        L3["L3 - Shared\nCross-agent namespace\nFederated swarm reads"]
    
        L0 -->|promoted| L1 --> L2 --> L3
    
        style L0 fill:#00D2AA11,stroke:#00D2AA
        style L1 fill:#F59E0B11,stroke:#F59E0B
        style L2 fill:#8B5CF611,stroke:#8B5CF6
        style L3 fill:#EF444411,stroke:#EF4444
    monomind memory store "key insight" --namespace my-project
    monomind memory search "auth implementation"     # BM25 + semantic hybrid

    πŸ—ΊοΈ Monograph β€” Your Codebase, as a Graph

    Before touching any file, Monomind queries Monograph β€” a SQLite-backed knowledge graph of your entire codebase. Nodes are files, classes, and functions. Edges are imports, calls, and dependencies.

    /mastermind:understand          # build the graph
    /mastermind:graph-status        # nodes Β· edges Β· freshness
    
    # Inside Claude Code, Monograph runs automatically:
    # β†’ "what files does auth.ts import?"
    # β†’ "what breaks if I change UserService?"
    # β†’ "find all callers of validateToken()"

    23 MCP tools. Impact analysis. Shortest-path queries. Community detection. Zero grep.


    🎣 Hooks & Workers

    Monomind wires 22 hook events into Claude Code. Every edit, task, command, and session fires hooks that log patterns, route agents, and train the intelligence system.

    flowchart LR
        CE["Claude Code\nEvent"] --> H["Hook Router"]
        H --> P["pre-edit\npre-task\npre-command"]
        H --> SS["session-start\nsession-end\nnotify"]
        H --> I["route\nlearn\nbuild-agents"]
        H --> T["teammate-idle\ntask-completed"]
    
        I --> DB[("AgentDB\npatterns.json")]
        DB -->|next session| CE

    12 background workers run continuously: security Β· health Β· swarm Β· learning Β· patterns Β· git Β· performance and more.


    πŸ›‘οΈ MonoFence AI β€” Security Layer

    Every agent boundary is defended by monofence-ai β€” real-time detection of prompt injection, jailbreaks, homoglyphs, base64 evasion, multi-turn escalation, and PII leakage.

    import { isSafe, createMonoDefence } from 'monofence-ai';
    
    isSafe('Ignore all previous instructions');  // β†’ false (~0.04ms)
    
    const fence = createMonoDefence({ enableContextTracking: true });
    const result = await fence.detect(userInput);
    // result.safe Β· result.threats Β· result.overallRisk

    πŸ“‹ 80+ Slash Commands

    Everything runs from inside Claude Code via slash commands. Here's the highlight reel:

    Development

    Command What it does
    /mastermind:autodev Autonomous research β†’ build β†’ review loop
    /mastermind:build Build a feature from a brief
    /mastermind:review Iterative review until zero findings
    /mastermind:debug Systematic root-cause debugging
    /mastermind:tdd Red β†’ Green β†’ Refactor
    /mastermind:architect Architecture review + file structure
    /mastermind:plan Comprehensive implementation plan
    /mastermind:worktree Feature work in isolated git worktree

    Organizations

    Command What it does
    /mastermind:createorg Design an autonomous agent org
    /mastermind:runorg Start it as a background daemon
    /mastermind:orgs List all orgs + status
    /mastermind:approve Action pending approval requests

    Business Domains

    Command What it does
    /mastermind:marketing Campaigns, copy, SEO, social
    /mastermind:content Blog posts, threads, newsletters
    /mastermind:sales Outreach, proposals, pipeline
    /mastermind:finance Budgets, invoicing, modeling
    /mastermind:ops Operations and workflow automation

    β†’ Full reference (80+ commands)


    πŸ“¦ Packages

    Package npm Purpose
    monomind npm Umbrella β€” install this one
    @monoes/monomindcli npm CLI engine (41 commands)
    monofence-ai npm AI manipulation defence
    @monoes/monograph npm Code knowledge graph

    πŸ—οΈ How It's Built

    graph TD
        CC["Claude Code"]
        MCP["MCP Server\nmonomind mcp start"]
        D["Background Daemon\n12 workers"]
    
        CC <-->|"23 tools: monograph, memory, swarm"| MCP
        MCP <--> D
    
        D --> ADB[("AgentDB\nSQLite + HNSW")]
        D --> MG[("Monograph\ncode graph")]
        D --> HK["Hooks\n22 event types"]
        D --> SW["Swarm\n6 topologies\n5 consensus algos"]
    
        CC -->|"Task tool - spawns agents"| AG["Agent Swarm\narchitect, coder\ntester, reviewer\nsecurity, perf"]
        AG <-->|reads and writes| ADB
    
        style CC fill:#00D2AA22,stroke:#00D2AA
        style AG fill:#8B5CF622,stroke:#8B5CF6
        style ADB fill:#F59E0B22,stroke:#F59E0B

    Claude Code handles all execution. MCP tools only coordinate. Your data never leaves your machine.


    Resources


    Monomind
    Built with β™₯ by monoes Β· MIT License