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Integrations

Download the right Blueprint files for your tool.

Choose your editor, CLI, or local runtime, then copy the file into the place your tool already expects. Start with static files first, then add MCP when you want live doctrine lookup.

Key Facts

Live today
MCP + exports + docs
Setup style
Direct files + copy-paste
Main clients
Claude, Cursor, Copilot, Gemini, DeepSeek, Qwen
Live path
MCP + static files
Local path
Prompt packs + llms.txt
Use today
Live public surface

These are the live public surfaces you can rely on right now for setup, downloads, and doctrine retrieval.

/mcpPublic read-only MCP endpoint
/llms.txtGenerated discovery document
/agent-assets/[slug]Public downloadable artifacts
/for-agentsLive hub for agent setup
Best added later
Add these only if you actually need them

Most teams only need the files and MCP surface above. Add automation later if the manual path becomes a real bottleneck in practice.

Use the static files before reaching for an installer
Add MCP only when you want live retrieval during the session
Keep the setup simple: one file, one clear placement, no extra wrapper layer
What should I start with?

Start with the file that matches your tool: `.mdc` for Cursor, `blueprint-core.md` for Windsurf, `copilot-instructions.md` for GitHub Copilot, `GEMINI.md` for Gemini CLI, and the prompt packs for DeepSeek or Qwen. If you want one shared repo-level file first, use `AGENTS.md`.

When do I need MCP?

Use MCP when you want live retrieval of principles, clusters, examples, and assets during a session. If you only want persistent doctrine inside a repo or editor, the static files are enough to begin.

Can I use this without changing my whole workflow?

Yes. This page is built for minimal change. In most cases you only add one file to your repo or tool config, then keep working inside the client you already use.

Do these integration files send data back to AI Design Blueprint?

Static files (AGENTS.md, .mdc rules, copilot-instructions.md, prompt packs) are local files only — they send nothing. Retrieval MCP tools (list_principles, search_examples, etc.) fetch doctrine and examples — they are read-only. The optional feedback tools (report_value_event, submit_feedback) only run when your agent surfaces them and you confirm — they send only the structured fields you explicitly pass. Your proprietary code is never captured by the integration layer.

Recommended setup order

If you are setting this up from scratch, this order gets you to a working integration with the least friction.

1. Start with the file that matches your tool
2. Add AGENTS.md if you want one shared repo-level doctrine file
3. Use llms.txt as the lightweight discovery companion
4. Add MCP only when you want live retrieval during the session
5. Use prompt packs for local or open-weight runtimes
6. Only add extra automation if the manual path becomes the real bottleneck
Where each file goes

Keep the setup literal. Put the file where the tool already expects it, then add MCP later if you want live doctrine lookup.

AGENTS.md -> repo root
.cursor/rules/blueprint-doctrine.mdc
.windsurf/rules/blueprint-core.md
.github/copilot-instructions.md
GEMINI.md -> repo root
MCP config -> client settings

Choose by tool type

Start with the tools already covered here, then expand only if you need a more specific path.

Tier 1
Primary editors and clients
AnthropicClaude CodeCursorCursorWindsurfWindsurfGithubCopilotGitHub CopilotGemini CLIGemini CLIOpenAICodex
Tier 2
Local and cross-tool
DeepSeek
Qwen
AGENTS.md
llms.txt
Tier 3
Additional clients
Continue
JetBrains AI Assistant
Aider
For agents
For agents

Live hub for MCP, assets, and current setup guidance.

For agents
Runtime architecture
Runtime architecture

When the problem becomes runtime, scheduling, and operational safety.

Runtime architecture
GitHub
GitHub

Provider files, shared instruction files, and setup docs — all public at github.com/aidesignblueprint.

View on GitHub
Pricing
Pricing

Where the public surface ends and the protected layer begins.

Pricing