Mcp Server Quest — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Mcp Server Quest (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Comprehensive quest orchestration system with KĀDI broker integration, replacing mcp-shrimp-task-manager with enhanced multi-channel approval workflow and document-driven development.
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.
.quest-data/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=devYou 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).
Build (as above). Running the packaged start script will initialize the data layer and built-in templates:
npm start
# or
node dist/mcp-server.jsNote: 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.
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.tsFor iterative development of the tools and integrations, run your dev server/process that wires the tools into an MCP transport when needed.
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.
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 filesNote: 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).
(unchanged — tool list retained in source)
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 monitoringquest_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 questquest_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 implementationquest_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 statusquest_workflow_guide: Get quest workflow documentation and guidanceBuilt to replace mcp-shrimp-task-manager with:
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.
agent.json highlights (located at project root)
Build configuration (used for image builds)
Deploy (example akash-mainnet target)
Runtime environment variables
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.
MIT
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