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aidesignblueprint/integrations

by Various

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

A

MCP

aidesignblueprint/integrations

Added 1 June 2026

Overview

This repository provides official integrations and installable doctrine for AI Design Blueprint, including MCP, IDE rules, prompt files, and agent runtimes. It is built in Python and serves as a structured collection for developers using the blueprint framework.

Best for

Best for
Developers building on AI Design Blueprint who need pre-built integration components

Use cases

  • Setting up MCP integrations for AI Design Blueprint
  • Configuring IDE rules to standardize AI development workflows
  • Deploying prompt files and agent runtimes from a single source

How to use

Tested with

Cursor, Windsurf

Example client config

{\n  "servers": {\n    "aidesignblueprint/integrations": {\n      "url": "https://aidesignblueprint.com/mcp"\n    }\n  }\n}

Notes

This repository provides official integrations and installable doctrine for AI Design Blueprint, including MCP, IDE rules, prompt files, and agent runtimes. It is built in Python and serves as a structured collection for developers using the blueprint framework.

2 stars on GitHub. Last updated 2026-05-28. Licensed MIT.

Use cases

  • Setting up MCP integrations for AI Design Blueprint
  • Configuring IDE rules to standardize AI development workflows
  • Deploying prompt files and agent runtimes from a single source

Pros

  • Official and curated integrations for the blueprint
  • Covers multiple integration types in one repository
  • Open source with Python base for easy customization

Cons

  • Very low star count suggests limited community adoption
  • May lack extensive documentation or examples
  • Narrow focus on the AI Design Blueprint only

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Official and curated integrations for the blueprint
  • Covers multiple integration types in one repository
  • Open source with Python base for easy customization

Cons

  • Very low star count suggests limited community adoption
  • May lack extensive documentation or examples
  • Narrow focus on the AI Design Blueprint only

Pairs with

Other entries in the index that connect to this one. Click through to see the chain.

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