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aidesignblueprint/integrations

the industry standard reference for safe, observable, and steerable AI agent UX. Browse and search 10 principles, clusters, curated implementation examples, and application guides for production agentic AI systems. 13 public tools require no credentials. `https://aidesignblueprint.com/mcp`

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About aidesignblueprint/integrations

aidesignblueprint/integrations is an MCP server in the Agents category: the industry standard reference for safe, observable, and steerable AI agent UX. Browse and search 10 principles, clusters, curated implementation examples, and application guides for production agentic AI systems. 13 public tools require no credentials. `https://aidesignblueprint.com/mcp`.

Install

From source
git clone https://github.com/aidesignblueprint/integrations

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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  • ✓README presentThe repository ships documentation.

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README

AI Design Blueprint Integrations

integrations MCP server

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

  1. Pick a setup guide in docs/setup/.
  2. Add the relevant file or MCP config to your own repository or client.
  3. If using MCP, initialize against https://aidesignblueprint.com/mcp.
  4. Run the first proof call:
    • clusters.list()
  5. 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):

[![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:

[![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.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About aidesignblueprint/integrations

How do I install aidesignblueprint/integrations?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is aidesignblueprint/integrations safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is aidesignblueprint/integrations still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.