moo-tasks
Enables Codeium agents to orchestrate tasks and goals with dependency tracking, human-in-the-loop blocking, and proof-of-work verification.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@moo-tasksplan tasks for integrating Stripe payments with acceptance criteria"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
š® Moo Tasks
Agentic Task Orchestration & Management Engine built for AI coding agents (Claude Code, Cursor, Windsurf, Antigravity, Copilot) and human-in-the-loop pair programming.
Quick Start ⢠Agent Setup ⢠Agent Protocol ⢠Architecture ⢠MCP Tools
š Why Moo Tasks?
Standard AI coding agents often suffer from:
Scope Drift: Wandering away from original user intent into endless low-value refactorings.
Over-Planning: Generating 40 shallow tasks without executing any of them.
Looping / Thrashing: Attempting the same failed fix repeatedly without stopping.
Unverifiable Work: Claiming code is complete without running tests or producing evidence.
Re-Debating Decisions: Re-arguing settled architectural choices on every context reset.
Moo Tasks solves this by providing a local SQLite engine (WAL mode), a rich real-time Web UI, and a Model Context Protocol (MCP) server that enforces strict enterprise invariants at runtime.
Related MCP server: agentloop
⨠Key Capabilities & Feature Matrix
šÆ 1. Goals & Scope Control
Verbatim Human Prompts: Sits above tasks, preserving the exact original user request.
Goal Coverage & Loose Ends: Live metrics on task completion percentage and lingering open tasks.
Scope Drift Detection: Automatically identifies and flags orphan tasks with no linked goal.
Goal Open Caps: Hard cap on maximum open tasks per goal (default: 10), preventing agents from over-planning.
Cascade Operations: Atomically drop, kill, or reopen all tasks under a goal with mandatory reasons.
š 2. Task Lifecycle & DAG Dependencies
Subtask Nesting Constraint: Exactly 1 level of subtasks under a parent task.
Finite State Machine:
todo,doing,blocked-on-dependency,waiting-on-human,done,dropped.DAG Dependency Graph: Automatic cycle detection and automatic unblocking of downstream tasks.
Parent Closure Guard: Prevents closing parent tasks while any subtask remains open.
Status Undo & History: Roll back accidental state transitions using full transition audit history.
š”ļø 3. Completion, Verification & Proof of Work
Acceptance Criteria: Mandatory criteria written in Markdown before work starts.
Evidence Requirement: Closing a task requires verifiable proof (commands run, stdout output, test proofs).
Two-Phase Verification: Distinguishes
agent_completedfrom humanverified_done.Rejection with Reason: Humans or peer agents can reject completed work with feedback; the task reverts to
todoand increments the reopen counter.
š 4. Human Collaboration & Blocking
Waiting-on-Human Queue: Agents pause blockers with attached questions (
clarification,approval,credential,decision).Reactive Resume: Answering a question via Web UI or MCP automatically transitions the task back into the ready queue without agent restarts.
Dedicated Human Inbox: Real-time queue of everything needing human attention.
š 5. Discovered Work
Mid-Task Work Capture: Capture new work found mid-flight without relinquishing current task claim.
Must-Fix vs Deferred: Mark as
must-fix-now(inserted as blocker) ordeferred(backlog pile).
š¤ 6. Ownership, Concurrency & Leases
Exclusive Task Claims: Leases with automatic timeout (default 5 minutes) when agents go silent.
Heartbeat Mechanism: Extend leases during long-running tasks.
Agent Concurrency Limits: Cap simultaneous tasks held per agent (default: 1).
File Touch Conflict Warnings: Declared files are checked for overlaps against other active claims.
š 7. Stall & Thrash Detection
Attempt Counter: Incremented on each claim/attempt.
Auto-Escalation: After $N$ attempts (default: 3), automatically pauses task to
waiting-on-humaninstead of endless looping.Time-in-State Tracking: Audits time spent in
doingand detects repeated reopens.
šļø 8. Settled Architectural Decisions (ADR)
Project-Level Record: Preserves choices and rationales that outlive tasks.
Pre-Planning Consultation: Agents read settled decisions before planning.
Supersede Support: Cleanly update and link superseded decisions with mandatory reasons.
š Quick Start & Installation
Option A: Install Globally (Recommended for moo command)
Install moo-tasks globally to access the short moo command anywhere:
npm install -g moo-tasks
# or: pnpm add -g moo-tasks | bun add -g moo-tasksOnce installed, you can use moo directly:
moo init # Initialize .moo workspace in current project
moo start # Launch real-time Web UI (http://127.0.0.1:4242)
moo ws # List registered global workspaces
moo status # Show Where-Did-I-Leave-Off context
moo search # Full-text SQLite searchš” Note on
moovsnpx:
Bare
moo <command>works when installed globally vianpm install -g moo-tasks.If running without global installation, use
npx moo-tasks <command>(do not usenpx moo, asmooon npm registry is an unrelated package).If
moo: command not foundappears after global install, ensure npm's global bin directory is in your$PATH:export PATH="$(npm prefix -g)/bin:$PATH"
Option B: On-Demand via npx moo-tasks
Run directly without global installation:
1. Initialize Workspace & Agent Protocols
Run in your project root:
npx moo-tasks initThis:
Initializes
.moo/tasks.dbSQLite database with WAL mode.Generates
AGENTS.md,CLAUDE.md,.cursorrules, and.windsurfrules.
2. Launch Local Web UI
npx moo-tasks startOpen http://127.0.0.1:4242 in your browser.
To access the Web UI from another device or tablet on your local network (LAN):
npx moo-tasks start --lan
# Automatically logs: http://192.168.x.x:4242/š Agent & MCP Setup
One-Command Multi-Agent Installer
# Configure all detected agent IDEs at once:
npx moo-tasks install all
# Or configure specific clients:
npx moo-tasks install claude # Updates ~/.claude.json
npx moo-tasks install cursor # Generates .cursor/mcp.json
npx moo-tasks install windsurf # Updates ~/.codeium/windsurf/mcp_config.json
npx moo-tasks install antigravity # Generates .gemini/settings.jsonManual Configuration
{
"mcpServers": {
"moo-tasks": {
"command": "npx",
"args": ["moo-tasks", "mcp"]
}
}
}š¤ Mandatory Agent Protocol
All AI coding agents are instructed to follow this 6-step lifecycle:
1. SESSION RESUME ā Call moo_session_resume() & moo_list_decisions()
2. ANCHOR GOAL ā Call moo_create_goal(title, verbatimPrompt)
3. PLAN & CRITERIA ā Call moo_create_task() with markdown criteria BEFORE code
4. EXCLUSIVE CLAIM ā Call moo_claim_task(taskId, agentId, sessionId)
5. IMPLEMENTATION ā If blocked, call moo_ask_human() or link blockers
6. VERIFIED PROOF ā Call moo_complete_task() with test proof & output snippet
7. ADR RECORD ā Call moo_record_decision() for architectural choicesš ļø MCP Tool Reference
Tool Name | Purpose |
| Record human's verbatim prompt and set open task cap |
| List project goals and statuses |
| View goal coverage, open vs cap, and loose ends |
| Drop goal and cascade drop all child tasks with reason |
| Reopen goal and its tasks |
| Create task under goal with acceptance criteria & declared files |
| Batch create multiple tasks atomically |
| ā” 1-call express vibe tool: Atomically creates and claims task with lease and declared files |
| ā” Fast progress checkpoint: Appends attempt note & extends heartbeat |
| š§ Ultra-dense token-optimized context block (< 400 tokens) for prompt injection |
| Update title, criteria, priority, declared files, or goal |
| Link prerequisite blockers with cycle validation |
| Unlink prerequisite blocker |
| Auto-surface next unblocked, highest-priority task |
| Get full task details, subtasks, notes, dependencies |
| Filter tasks by goal, status, priority, agent, deferred |
| Exclusively claim task (enforces lease & conflict checks) |
| Extend active lease during long-running tasks |
| Voluntarily release claim back to todo |
| Handoff in-flight task to another agent with notes |
| Mark task done with mandatory commands/proof evidence |
| Verify task done (human or verification agent) |
| Reject completed task with mandatory reason |
| Escalate question to human and pause task |
| List all tasks waiting on human guidance |
| Answer question and auto-resume task |
| Add discovered work (must-fix or deferred) |
| Append timestamped, attributed context/attempt note |
| List context history and attempt logs |
| Drop task with mandatory reason |
| Reopen task without losing audit history |
| Undo last status transition |
| Drop multiple tasks in single operation |
| Reopen multiple tasks in single operation |
| Record project-level architectural decision |
| List settled decisions before planning |
| Supersede decision with new rationale |
| Merge duplicate tasks |
| "Where did I leave off?" session summary |
| Export project to Markdown, JSON, or Plain Text |
| Archive done/dropped tasks out of active list |
šļø Architecture & Clean Code
src/
āāā domain/ # Pure Enterprise Domain Rules & Invariants
ā āāā types.ts # Domain interfaces & value types
ā āāā errors.ts # Domain-specific typed error classes
ā āāā dependency.ts # DAG cycle detector & unblocked evaluator
ā āāā conflict.ts # File touch overlap conflict detector
ā āāā similarity.ts # Duplicate task similarity detector
ā
āāā infrastructure/ # Persistence & External Integrations
ā āāā db/database.ts # SQLite manager (WAL mode, busy timeout)
ā āāā db/migrations.ts # Schema DDL and versioning
ā āāā git/git-context.ts # Git branch, commit, dirty status extractor
ā āāā repositories/ # SQLite Repository Implementations
ā
āāā services/ # Application Services (Use Cases)
ā āāā goal-service.ts # Goal lifecycle & cap enforcement
ā āāā task-lifecycle-service.ts # State machine, ready queue, undo
ā āāā claim-service.ts # Exclusive claims, leases, dead-agent timeout
ā āāā verification-service.ts# Proof of work & two-phase verification
ā āāā human-collab-service.ts# Human Q&A queue & reactive resume
ā āāā discovered-work-service.ts # Mid-flight discovered work
ā āāā decision-service.ts # ADR logs & supersede linking
ā āāā duplicate-merge-service.ts # Idempotency & task merging
ā āāā session-service.ts # Where-did-I-leave-off session resume
ā āāā housekeeping-service.ts# Archiving & multi-format export
ā āāā index.ts # Dependency Injection Container
ā
āāā mcp/ # Model Context Protocol Stdio Server
āāā server/ # Fastify HTTP + Server-Sent Events (SSE) Engine
āāā cli/ # CLI Commands (start, init, install, mcp)
āāā ui/ # Vanilla JS + Tailwind + Lucide Icons Web UIš¤ Contributing
Contributions are welcome! Please check out CONTRIBUTING.md for development setup, testing, and PR guidelines.
š License
This project is licensed under the MIT License.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseNot gradedqualityAmaintenanceServer-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce ā the server blocks the call if they don't. Works with any MCP-compatible client.199MIT
- AlicenseNot gradedqualityAmaintenanceMCP server that enables AI agents to run a deterministic orchestration loop with decomposition, subagent execution, and review feedback across multiple LLM backends.54MIT
- AlicenseNot gradedqualityCmaintenanceMCP server for task management that enables AI agents to read, create, update tasks, and track work sessions, allowing agents and humans to collaborate on the same task board.27MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to manage hierarchical tasks, track progress, handle dependencies, and coordinate work through an MCP server.5715GPL 3.0
Related MCP Connectors
MCP server for AI agents to plan, verify, and deploy Cloudflare-native apps.
Control plane for autonomous software labor. Agents claim objectives over MCP with audit trail.
MCP server for generating rough-draft project plans from natural-language prompts.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/shekarsiri/moo-tasks'
If you have feedback or need assistance with the MCP directory API, please join our Discord server