mk-spec-master 0.3.2

MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach (AI 規格大師)

MK Spec Master

AI 規格大師 — specs in, scenarios out. Bidirectional traceability so you always know what's tested.

English · 繁體中文

Spec-driven testing over MCP. Turn Linear / JIRA / GitHub Issues / Notion / Figma / Markdown specs into runnable scenarios, hand off to any test runner via mk-qa-master, and keep a live spec ↔ test coverage matrix.

🟢 Alpha — v0.3 partial. 12 tools + 6 adapters. Full design in docs/prd.md. Still pending for v0.3: optimization plan + spec-knowledge layer.

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Install

uvx mk-spec-master    # or: pip install mk-spec-master

Add to your MCP client config:

{
  "mcpServers": {
    "mk-spec-master": {
      "command": "uvx",
      "args": ["mk-spec-master"],
      "env": {
        "SPEC_SOURCE": "markdown_local",
        "SPEC_PROJECT_ROOT": "/path/to/your/project"
      }
    }
  }
}

Then in Claude / Cursor / Codex / Gemini CLI:

"Use mk-spec-master to parse SPEC-001, extract scenarios, and hand them to mk-qa-master so we can generate Playwright tests."

What this is

An MCP server that turns specs — Linear tickets, JIRA stories, GitHub Issues, Notion pages, Figma annotations, plain Markdown — into structured test scenarios, hands them to any test runner (via mk-qa-master or directly), and maintains a live spec ↔ test coverage matrix.

Sibling to mk-qa-master in the mk-* family of opinionated AI-QA MCPs.

Why this is missing from the ecosystem

Tool	Lock-in	What we do differently
AWS Kiro	AWS IDE only, proprietary	MCP-native, multi-client, open source
Jama Connect MCP	$50k+/year, enterprise-only	SMB / indie / AI-native segment
GitHub Spec Kit	spec→code; runtime test coverage out of scope	We add runtime test coverage
testomat.io / JIRA MCPs	Single source (JIRA), SaaS lock	Multi-source, file-based index, no lock

See docs/prd.md §4 for the full positioning.

Tool surface (v0.2 partial — 10 tools)

Tool	Since	Purpose
get_spec_source_info	v0.1	Active adapter + all available — call this first
list_specs	v0.1	Enumerate specs from the active source (filter by status / label / limit)
fetch_spec	v0.1	Pull a single spec's full content by id
parse_spec	v0.1	Heuristic AC extraction (en + zh-TW + zh-CN headings supported); accepts spec_id or raw_text
extract_scenarios	v0.1	AC → scenarios with happy / edge / error classification (negation-aware) and best-effort Given/When/Then split
generate_test_plan	v0.1	One-shot fetch + parse + extract → markdown plan ready to feed to mk-qa-master.generate_test(business_context=...)
link_test_to_spec	v0.1	Record that a test verifies a spec (writes to SPEC_PROJECT_ROOT/.mk-spec-master/index.json). v0.2: caches title / source / url for the matrix
get_coverage_matrix	v0.2	Spec × test grid — answer "which specs have no tests" in one call
analyze_spec_quality	v0.2	Heuristic coach — flags vague language, implementation-leak AC, unclear role refs (the differentiator vs Kiro / Spec Kit)
propose_spec_improvements	v0.2	Take analyze output → PM-facing markdown with concrete rewrites
get_drift_report	v0.2.1	For every spec with a stored ac_hash, fetch live + recompute + compare. Buckets results into fresh / drifted / unknown / stranded
auto_link_tests	v0.3.2	Scan a test directory for @spec: <ID> tags in docstrings or comments and link them automatically. Python / JS / TS / Go supported. dry_run previews without writing

Still pending for v0.3: optimization plan + spec-knowledge layer.

Adapter status

SPEC_SOURCE	Source	Status	Auth
markdown_local	Local *.md with YAML-ish frontmatter	✅ since 0.1.0	none
github_issues	GitHub Issues via gh CLI	✅ since 0.1.0	gh auth login or GITHUB_TOKEN
linear	Linear API (GraphQL)	✅ since 0.2.2	LINEAR_API_KEY + SPEC_PROJECT_KEY=<team-key> (optional)
jira	JIRA Cloud (REST v3, ADF → markdown)	✅ since 0.2.3	JIRA_BASE_URL + JIRA_EMAIL + JIRA_API_TOKEN + SPEC_PROJECT_KEY=<project-key> (optional)
notion	Notion databases (REST v1, blocks → markdown)	✅ since 0.3.0	NOTION_TOKEN + SPEC_PROJECT_KEY=<database-id>
figma	Figma file frames (TEXT nodes + comments → markdown)	✅ since 0.3.1	FIGMA_TOKEN + SPEC_PROJECT_KEY=<file-key>

v0.2 complete in 0.2.3. v0.3.0 added Notion; v0.3.1 Figma; v0.3.2 auto_link_tests. Optimization plan + spec-knowledge layer still pending.

Walkthrough — spec → test → coverage

Given a Linear ticket LIN-123 "Apply discount at checkout" with 4 acceptance criteria:

You: Use mk-spec-master to fetch LIN-123, extract scenarios, generate
     Playwright tests with mk-qa-master, run them, and report coverage.

The AI client chains:

mk-spec-master.fetch_spec("LIN-123")
mk-spec-master.parse_spec(spec_id="LIN-123")        → 4 AC
mk-spec-master.extract_scenarios(...)                → 1 happy + 3 error
mk-spec-master.generate_test_plan(spec_id="LIN-123")

for scenario in plan:
  mk-qa-master.generate_test(business_context=scenario.gherkin)
  mk-spec-master.link_test_to_spec(spec_id="LIN-123", test_node_id=...)

mk-qa-master.run_tests

The traceability index now records all 4 links. Next sprint, when the spec changes, get_drift_report (v0.2) will flag tests that may be stale.

Status

Milestone	Target	Status
v0.1 (MVP — markdown_local + github_issues, 7 tools)	June 2026	✅ Shipped
v0.2 (Linear, JIRA, coverage matrix, spec-quality coach, drift report)	Aug 2026	✅ Complete (0.2.3)
v0.3 (Notion, Figma, auto-link, optimization plan)	Oct 2026	🟡 Notion + Figma + auto-link shipped (0.3.2); optimization plan pending
v1.0 (production-ready, docs, integration recipes)	Q4 2026	⬜

Family

• mk-qa-master — AI 測試大師, the test-runner sibling. Tests run via mk-qa-master; coverage tracked here.
• More mk-* MCPs in design (mk-perf-master, mk-a11y-master).

License

MIT © 2026 Jack Kao — see LICENSE (中文翻譯參考：LICENSE.zh-TW.md; the English version is authoritative).

Plain-English version: personal use, commercial use, modification, redistribution — all allowed. The only requirement is that you keep the copyright and license notice in your copy. No warranty: if it breaks something in production, you can't come after the author.

If this saved you time, a coffee goes a long way. ☕