integrations
Official integrations and installable doctrine for AI Design Blueprint: MCP, IDE rules, prompt files, and agent runtimes.
Install / Use
claude mcp add aidesignblueprint -- npx -y github:aidesignblueprint/integrationsIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AI & Machine LearningSupported Platforms
Our assessment of integrations
integrations scores 76/100 on our quality scale, 619th of 762 AI & Machine Learning skills we index.
Its MCP Server is 5.0 KB long, well organised into 12 sections with 2 code examples: a solid amount of guidance for an agent.
It has 3 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated 2 days ago, so integrations is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 92/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
integrations compared with similar skills
All 4 of these similar skills score higher than integrations; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| integrations (this skill)by aidesignblueprint | 76 | 3 | 2d ago | MCP Server |
| claude-memby thedotmack | 100 | 94.8k | 1d ago | CLAUDE.md |
| Agent-Reachby Panniantong | 100 | 85.7k | 12d ago | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 84.3k | 15d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 73.9k | today | CLAUDE.md |
Frequently asked questions
- How do I install integrations?
- Run
claude mcp add aidesignblueprint -- npx -y github:aidesignblueprint/integrations. The install tabs above show the steps for each supported agent. - Which AI agents does integrations work with?
- It is written for Claude Code, Claude Desktop and Cursor, as a MCP Server file. Other agents that read the same format can often use it too.
- Is integrations safe to use?
- It is MIT-licensed and scores 92/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is integrations still maintained?
- The repository was last updated 2 days ago, so integrations is actively maintained.
Skill content
View source on GitHubAI 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 filesmcp/: public MCP configuration and usage notesdocs/setup/: copy-first setup guides by toolcursor/,windsurf/,github-copilot/,gemini/: provider-specific instruction filesopen-weights/: static prompt packs for open-weight and local model workflowsexports/: 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 silentlysignals.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; scores agentic code against the 10 principles; setprivate_session=trueto skip the stored run for that calldesign.validate(implementation_context, ..., private_session?)— Pro/Teams; the surface mirror: scores a rendered frontend artefact against the 8 experience-design laws (own weekly bucket)spec.validate(implementation_context, ..., private_session?)— Pro/Teams; the what-to-build lens: scores a written specification against the 8 spec-quality laws (own weekly bucket)team.summarize(days_back?, private_session?)— Pro/Teams; usage reflection and recommended next assets across all three validator lensesme.add_evidence(course_slug, stage_id, note)
Feedback and value signal rules
- Only call
signals.reportafter 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.feedbackwhen 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):
[](https://aidesignblueprint.com)
Pro badge — run architect.validate() via the MCP. The response includes run_id, badge_url, and review_url:
[](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.
Related Skills
claude-mem
94.8kPersistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More
Agent-Reach
85.7kGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
Understand-Anything
84.3kGraphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
headroom
73.9kCompress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
