"Spec-WorkFlow documentation or implementation" matching MCP servers:

A methodology and MCP server for agent-driven software development where humans write specs and agents implement code, enforced by six mechanical gates to ensure spec validity, contracts, tests, and review.

Provides MCP tools to score request sufficiency against a profile, block underspecified work, and write committed decision records with evidence and overrides.

Streamlines development workflows through AI-assisted codebase analysis, comprehensive planning, task breakdown with dependencies, and automated implementation verification. Enables systematic approach to complex development tasks like framework migrations and feature implementation.

A standalone runtime and MCP server that executes Claude Code dynamic workflow files through interchangeable agent providers, ensuring compatibility with Claude Code's workflow format.

Enables deterministic, resumable workflow automation through DAG step graphs, boolean gate branching, automatic parallel execution, and in-step agent loops with sandboxed file and command tools.

Enables bounded, multi-phase coding workflows inside Codex that plan, implement, independently review, repair, and verify repository changes, with an inline dashboard for inspecting runs.

Enables multi-agent code review and iterative improvement loop using different LLM backends, with deterministic scoring and audit trail.

Enables 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.

Enables building LangGraph projects by editing a structured YAML spec, with MCP tools for scaffolding, adding nodes/edges, validating, and deterministically rendering Python graph code.

Enables agentic coding clients to enforce portable policy guardrails by evaluating proposed shell, file write, git, and network actions and returning allow, deny, or ask decisions.

Delegates autonomous coding tasks to Z.ai's GLM models with a genuine agent loop, file operations, and verification via git and real process results.

Enables AI agents to create, share, discover, and execute reusable multi-step workflow templates.

Enables agents to classify and prioritize tickets, emails, and logs, apply auditable business rules, and trigger actions safely with dry-run and live-mode safeguards.

A production-grade multi-agent workflow orchestrator built on the Model Context Protocol, featuring planner/executor/critic agents, durable run state, and replayable traces.

Enables enterprise multi-agent decision workflows that expose 8+ MCP tools such as SQL query, web search, Python sandbox, RAG, file access, data cleaning, chart generation, and HTTP calls, orchestrated with LangGraph, streaming output, and human-in-the-loop approvals.

Enables deterministic, step-by-step execution of YAML-defined skills and workflows for AI agents, with progressive disclosure of active-step instructions and tools. It manages workflow state, conditional DAG transitions, loops, and persistent sessions via start_workflow, next_step, and end_workflow.

QA bug-fix workflow MCP server that waits for bug reports with source locations, enables Claude Code to automatically fix bugs, and cycles through pending issues.

An MCP server implementation that enables calling iFlytek workflows through the Model Context Protocol, allowing for intelligent workflow scheduling with sequential, parallel, loop, and nested execution modes.

Enables AI agents to commit stateful workflow checkpoints by calculating state hashes and rollback points through the Model Context Protocol. It provides deterministic, dependency-free checkpoint management for autonomous agent execution.

Enables AI agents to capture and commit stateful workflow checkpoints during autonomous execution, computing deterministic state hashes and rollback points. It runs as a zero-dependency Python MCP server that plugs into Claude Desktop, Cursor, and other MCP-compliant clients for reliable, low-latency checkpoint management.