mcp-server-quest
Comprehensive quest orchestration system with KĀDI broker integration, multi-channel approval workflow, and Git-backed data storage.
README
mcp-server-quest
Comprehensive quest orchestration system with KĀDI broker integration, replacing mcp-shrimp-task-manager with enhanced multi-channel approval workflow and document-driven development.
Overview
mcp-server-quest is an MCP-related package that provides tooling for managing quests, tasks, agents, and approvals (tool implementations live in src/tools). IMPORTANT: this package now focuses on bootstrapping the data layer (Git-backed quest data repository and built-in templates) and initializing runtime templates. The entry point (src/index.ts) initializes the .quest-data/ Git repo and built-in templates; it does not itself host the dashboard UI and does not automatically start an MCP HTTP server. The dashboard UI is served by the separate mcp-client-quest package or by a separate runtime that exposes MCP endpoints.
Key Features
- Quest Management: Create, revise, and manage quests with automatic task splitting
- Two-Tier Approval: Quest-level and task-level approval gates
- Multi-Channel Approvals: Discord, Slack, and Dashboard integration (UI provided by mcp-client-quest)
- Task Orchestration: Assign tasks to agents with dependency validation
- File-based Storage: Git-versioned data in
.quest-data/ - KĀDI Integration: Tool implementations use @modelcontextprotocol/sdk for broker interactions
- Data Layer Bootstrap: Initializes Git repo and built-in quest templates on startup
Installation
Recommended build/install steps (matches agent.json build/run):
# Install deps (including dev deps, required for build)
npm ci --include=dev
# Build the project (TypeScript)
npx tsc
# Optionally prune dev deps for production image
npm prune --omit=dev
You can still install and build locally with the simpler commands for development, but the image build uses the sequence above.
The project build configuration is set up to produce a production image from node:20-alpine (see agent.json build section).
Quick Start
Start (production)
Build (as above). Running the packaged start script will initialize the data layer and built-in templates:
npm start
# or
node dist/mcp-server.js
Note: Running the start script (dist/mcp-server.js) runs the initialization (Git repo + templates) and graceful shutdown handlers. It does not, by itself, start an HTTP MCP transport or dashboard UI. To run a full MCP server that exposes HTTP transport and serves endpoints, use a runtime that wires the tool implementations into an MCP server or run a companion package that provides the transport layer.
Development
You can run the TypeScript sources directly with your preferred dev tooling (e.g., tsx or nodemon) to execute the initialization flow defined in src/index.ts:
# Example with tsx (if installed)
npx tsx src/index.ts
For iterative development of the tools and integrations, run your dev server/process that wires the tools into an MCP transport when needed.
Dashboard Access
The dashboard UI is provided by the mcp-client-quest package. The client connects to an MCP transport endpoint (HTTP or broker) where an MCP server/runtime exposes the tool endpoints. This repository does not include the dashboard frontend.
Architecture
- Node.js: Built for Node 20 (container image uses node:20-alpine)
- TypeScript: 5.3+ with strict mode
- MCP Protocol: Tool implementations use @modelcontextprotocol/sdk for broker-driven interactions
- Express: Present as a dependency in the project, but this package's entry point focuses on data bootstrap rather than serving HTTP endpoints by default
- Deploy/build behavior is configured via agent.json; deployments may expose an HTTP port for MCP transport (see Configuration)
Project Structure
mcp-server-quest/
├── src/
│ ├── index.ts # Entry point: bootstraps data layer and initializes templates
│ ├── tools/ # MCP tool implementations
│ ├── models/ # Quest, Task, Agent, Approval models (including TemplateModel)
│ ├── prompts/ # Document generation prompts
│ └── utils/ # Shared utilities (git repo init, config)
├── .quest-data/ # Git-versioned quest data (initialized at startup)
└── tests/ # Test files
Note: The dashboard UI and WebSocket client are provided by the mcp-client-quest package; this repository initializes the quest data repo and built-in templates (see src/index.ts).
MCP Tools (26 total)
(unchanged — tool list retained in source)
Agent Management (4)
quest_register_agent: Register an agent with capabilitiesquest_unregister_agent: Remove an agent from the systemquest_list_agents: List all registered agentsquest_agent_heartbeat: Agent heartbeat for health monitoring
Quest Lifecycle (6)
quest_create_quest: Create a new quest with requirements and designquest_query_quest: Query quest info (detail="summary" for progress, detail="full" for complete data)quest_list_quest: List all quests with optional status filter and paginationquest_update_quest: Revise quest requirements and designquest_archive_quest: Archive a questquest_delete_quest: Permanently delete a quest
Task Management (11)
quest_split_task: Split quest into implementation tasksquest_assign_task: Assign tasks to agentsquest_query_task: Query tasks by ID (full details) or search/filterquest_update_task: Update task metadata and/or status (with agent authorization)quest_delete_task: Delete a taskquest_submit_task_result: Submit task implementation resultquest_verify_task: Verify task completionquest_log_implementation: Log implementation detailsquest_plan_task: Plan task implementation approachquest_analyze_task: Analyze task requirementsquest_reflect_task: Reflect on task implementation
Approval Workflow (4)
quest_request_quest_approval: Request human approval for a quest planquest_request_task_approval: Request human approval for a completed taskquest_submit_approval: Submit approval decision (approve/reject/revise)quest_query_approval: Check approval status
Workflow Guidance (1)
quest_workflow_guide: Get quest workflow documentation and guidance
Development
Built to replace mcp-shrimp-task-manager with:
- Enhanced approval workflow (Discord/Slack/Dashboard)
- Document-driven development (requirements.md, design.md)
- Improved task splitting with dependency validation
- Data-layer initialization (Git repo + built-in templates)
On startup the package initializes the Git-backed quest data directory and loads built-in templates (see src/index.ts). The dashboard frontend has been extracted to mcp-client-quest.
Configuration
agent.json highlights (located at project root)
- name: mcp-server-quest
- version: 0.1.0
- scripts.start: node dist/mcp-server.js
Build configuration (used for image builds)
- build.default.from: node:20-alpine
- build.default.cli: latest
- build.default.run: ["npm ci --include=dev", "npx tsc", "npm prune --omit=dev"]
- build.default.env: { "NODE_ENV": "production" }
Deploy (example akash-mainnet target)
- target: akash (akash-mainnet)
- engine: podman
- services.app.image: mcp-server-quest:0.1.0
- exposes port 3100 (mapped as service port, global)
- env defaults in deploy: MCP_TRANSPORT_TYPE=http, MCP_PORT=3100, NODE_ENV=production
- resources: cpu 0.5, memory 512Mi, ephemeralStorage 512Mi
Runtime environment variables
- MCP_TRANSPORT_TYPE: transport type (e.g., "http") — deployments/runtimes that expose MCP endpoints may use this
- MCP_PORT: HTTP port (default in deploy/config: 3100)
- NODE_ENV: production/development
Note: While the deployment configuration exposes port 3100 and provides MCP-related env defaults, this package's entry point focuses on data initialization. Running an MCP server that exposes HTTP endpoints requires wiring the tool implementations into an MCP transport/runtime.
License
MIT
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