Architect Agent Framework MCP Server
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- FlicenseCqualityBmaintenanceEnables AI agents to collaborate via shared blackboard state, multi-agent deliberation, human-in-the-loop proposal approval, operating-mode control, and audit logging through MCP.11-
- AlicenseNot gradedqualityBmaintenanceEnables MCP-capable AI agents to work on bounded project folders through read, write, run, and verify tools, with durable approval/resume workflows and completion proven by observed verification evidence rather than self-reported results.MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI coding providers to run structured multi-agent workflows with tracked tasks, specifications, handoffs, and health-gated completion. It exposes MCP tools for task claiming, action logging, repairs, document validation, and lifecycle evidence.29 npmMIT
- AlicenseNot gradedqualityCmaintenanceProvides MCP tools for AI agents to create and read decision decks, propose cards and build plans, and retrieve finished tasks, enabling local decision review workflows with portable task handoffs.2MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI coding providers to run structured multi-agent workflows with specification documents, tracked tasks, handoffs, health checks, and auditable repair modes through MCP tools. It coordinates task claims, action logs, lifecycle notices, and final completion evidence across supported providers.29 npmMIT
- AlicenseNot gradedqualityAmaintenanceEnables structured multi-agent workflows across AI coding providers by managing documents, tracked tasks, handoffs, health evidence, and MCP-owned task/action state. It supports spec creation, implementation coordination, review, triage, and health-gated completion.29 npmMIT
TDQS
Scored across 29 tools
The tool set has many similarly named lifecycle phases, especially architect_runs_start vs architect_runtime_start/plan, architect_sdd_check vs architect_style_check vs architect_candidate_review, and architect_runtime_status vs architect_runs_observe. Descriptions do clarify most boundaries, but an agent could still misselect among the runtime/run/review/check tools without careful reading.
Most tools follow an architect_<domain>_<action> snake_case pattern, with clear groupings for sdd, runtime, runs, task, and language. There are minor deviations such as architect_capabilities, architect_doctor, architect_console_url, and noun-first review names, but the overall convention is predictable.
With 29 tools, the surface is heavy and exceeds the typical well-scoped range. The domain is complex, but several tools cover narrow runtime phases or review/check states, making the overall set cumbersome for an agent to navigate.
The surface covers the SDD lifecycle from init and extraction through materialization, proposal, review, runtime execution, task leasing, diagnostics, and human handoff via the console URL. Minor gaps exist around explicit installation or broader workspace administration, but core workflows and human acceptance boundaries are represented.