AI Design Blueprint Integrations

Official integrations and installable doctrine for AI Design Blueprint across MCP, IDE rules, prompt files, and agent runtimes.

What is in this repo

shared/: cross-tool doctrine files
mcp/: public MCP configuration and usage notes
docs/setup/: copy-first setup guides by tool
cursor/, windsurf/, github-copilot/, gemini/: provider-specific instruction files
open-weights/: static prompt packs for open-weight and local model workflows
exports/: structured doctrine export

Public contract

Canonical public endpoints:

Site: https://aidesignblueprint.com
MCP: https://aidesignblueprint.com/mcp
Developer docs: https://aidesignblueprint.com/en/for-agents

Quick start

Pick a setup guide in docs/setup/.
Add the relevant file or MCP config to your own repository or client.
If using MCP, initialize against https://aidesignblueprint.com/mcp.
Run the first proof call:
- clusters.list()
Then run a second proof call:
- examples.search(query="orchestration visibility steering", limit=3)

Public MCP tools

Public retrieval tools (anonymous-allowed, read-only)

principles.list(cluster?)
clusters.list()
principles.get(slug)
clusters.get(slug)
examples.get(slug)
principles.search(query, limit?)
examples.search(query, principle_ids?, difficulty?, library?, limit?)
assets.list()
guides.list()
guides.get(slug)
guides.search(query, limit?)

Public signal tools (anonymous-allowed, opt-in write)

signals.report(event_type, surface_used?, brief_context?, perceived_value?, workflow_stage?, would_recommend?, team_size?) — records a value moment; only offer after the user clearly expresses something was useful; never call automatically or silently
signals.feedback(task_type?, surface?, rating_clarity?, rating_usefulness?, what_helped?, what_missing?, would_use_again?, contact_email?, permission_to_follow_up?) — explicit qualitative feedback; only call when the user explicitly asks to leave feedback

Signal tools write only the structured fields you pass. No prompts, no code, no file contents are stored. See the privacy policy for full data-handling details.

Protected tools (authenticated, not part of anonymous setup path)

me.learning_path()
me.coaching_context()
architect.validate(implementation_context, ..., private_session?) — Pro/Teams; set private_session=true to skip all server-side logging for that call
team.summarize(days_back?, private_session?) — Pro/Teams; usage reflection and recommended next assets
me.add_evidence(course_slug, stage_id, note)

Feedback and value signal rules

Only call signals.report after the user has clearly expressed that something was useful. Never call automatically or silently. Offer at most once per session after a clear success signal.
Only call signals.feedback when the user explicitly asks to leave feedback. Never prompt for it proactively.
Never include proprietary code, file contents, or secrets in brief_context.

Governance badges

Show that your agent or repo follows the Blueprint doctrine.

Free badge — paste into your README.md (no account required):

hljs language-markdown

[![AI Design Blueprint](https://aidesignblueprint.com/api/badge/free.svg)](https://aidesignblueprint.com)

Pro badge — run architect.validate() via the MCP. The response includes run_id, badge_url, and review_url:

hljs language-markdown

[![AI Design Blueprint](https://aidesignblueprint.com/api/badge/run/<run_id>.svg)](https://aidesignblueprint.com/en/readiness-review/<run_id>)

The Pro badge displays your tier (Governed · X/Y or Reviewed · X/Y) and links to a public readiness review page. Requires a Pro or Beta account.

What is intentionally not here yet

no public OpenAPI schema
no public HTTP API contract beyond MCP and static assets
no CLI installer
no speculative partner-specific distributions

Source of truth

This repo is intended to mirror the canonical public contract already shipped on aidesignblueprint.com.

Before publishing changes here, verify:

/mcp
/llms.txt
/agent-assets/[slug]
/en/for-agents

remain consistent with the files committed in this repo.

integrations