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Spring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
автор: Community
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Read-only doctrine access for the Agentic AI Blueprint — the industry standard reference for safe, observable, and steerable AI agent UX. Browse and search 10 p
Read-only doctrine access for the Agentic AI Blueprint — 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
Official integrations and installable doctrine for AI Design Blueprint across MCP, IDE rules, prompt files, and agent runtimes.
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 exportCanonical public endpoints:
https://aidesignblueprint.comhttps://aidesignblueprint.com/mcphttps://aidesignblueprint.com/en/for-agentsdocs/setup/.https://aidesignblueprint.com/mcp.clusters.list()examples.search(query="orchestration visibility steering", limit=3)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?)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 feedbackSignal 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.
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 callteam.summarize(days_back?, private_session?) — Pro/Teams; usage reflection and recommended next assetsme.add_evidence(course_slug, stage_id, note)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.signals.feedback when the user explicitly asks to leave feedback. Never prompt for it proactively.brief_context.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.
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-agentsremain consistent with the files committed in this repo.
Добавь это в claude_desktop_config.json и перезапусти Claude Desktop.
{
"mcpServers": {
"aidesignblueprint-integrations": {
"command": "npx",
"args": []
}
}
}