"Blackmagic Design" matching MCP servers:

Provides source-backed design context, route card validation, contract generation, critique and verification reports, evidence packages, Penpot change plans, and anti-repeat checks for design workflows. Does not directly mutate Penpot, but consumes read-only Penpot snapshots.

Design contract layer for AI agents. Scans Figma, code, Storybook, and token files, reconciles conflicts, and serves a single machine-readable source of truth so every agent gets the same authoritative design rules before it builds. Local-first.

MCP server bridging ChatGPT-compatible clients to the Design Flow System, enabling project session management, draft import, round locking, and read-only access to design state and traceability.

Enables storing and querying structured information about software code entities (classes, functions, files) and their relationships (calls, imports) along with qualitative observations like design decisions and change rationale.

A design knowledge MCP server that Claude can query when generating UI, covering eight layers: principles, patterns, content design systems, research methods, service design, brand/visual, business strategy, and design tokens.

Enables AI clients and agents to turn a new idea into a structured set of clarifying questions, technology options, upward design breakdowns, reverse reasoning, and risk assessments so users can steer top-level design decisions. It also supports saving insights and building a bidirectional design tree of concepts and their implementations.

Provides systematic thinking tools including mental models, design patterns, debugging approaches, and collaborative reasoning frameworks to enhance problem-solving and decision-making capabilities.

An MCP server that provides AI tools with relational tech principles, patterns, and the Studio library to guide builders in creating community-centered tools using embedded design.

Experimental load-path analysis for 3D-printed STL parts, with stress and movement comparisons across CAD revisions, PNG captures, visual reviews, and persistent human-guided design sessions. Runs locally through a stdio MCP server.

MCP server that provides access to over 100 development skills for frontend, backend, integration, design, devops, and process categories via Claude Code and other MCP clients.

Enables AI assistants to read Lanhu design collaboration content: extracting and analyzing Axure prototype pages, downloading UI designs and slices, and converting design specs into HTML+CSS for implementation. It also provides a shared team message board so multiple AI tools can reuse requirement analyses and knowledge across projects.

Provides local-first retrieval over long design conversations, enabling users to find where a decision was made, why, and what replaced it, with turn and line range citations through hybrid retrieval, typed judgment rerank, exact search, and five MCP tools.

Enables AI coding agents to access evidence-backed repository memory, code graph, project DNA, and deterministic change validation so they understand design decisions, past bugs, and invariants while working.

Enables querying a plant knowledge graph for companion planting, climate suitability, and landscape design recommendations via natural language.

MCP server exposing eight esoteric calculation systems (Western/Vedic astrology, Human Design, Gene Keys, and more) through 14 tools, with deterministic profiles, partial success, and OAuth integration.

Enables Claude Code to use local markdown notes as persistent, searchable memory with hybrid recall, episodic memory, note-graph traversal, design memory, and optional cloud sync.

Lets coding agents index and search local PDF books, retrieve relevant passages with citations, and persist design lessons for system design and implementation tasks.

MCP server that indexes and serves design skills, guides, and patterns from the taste-skill library, enabling structured retrieval and workflow prompts for design, redesign, and image generation.

Enables AI agents to store and retrieve design decisions as Markdown in git repositories, and check new proposals against historical decisions via MCP.

Enables MCP clients to search and read a local library of saved prompts, skills, MCP servers, and design boards, fill prompt blanks, and retrieve board design briefs through read-only, offline tools, prompts, and resources.

Reusable, read-only MCP server that exposes a repo's knowledge files (backlog docs, decisions, design notes) as MCP resources over stdio.

Enables AI agents to search a local SQLite knowledge base before fetching, save fetched documents with deduplication, and retrieve full text with metadata, preventing redundant fetches and fabrication.

Enables Claude to access and update a team's design knowledge stored in a local Markdown folder, including searching decisions and recording new conventions.

A lightweight MCP server that lets distributed AI agent teams query a designated project lead before making design decisions, preventing divergence.

Stores and searches AI-generated knowledge about software projects, enabling Cursor to access project structures, design patterns, best practices, and technical documentation.

An MCP server for saving project notes and design decisions to a SQLite database, with git-tracked storage and support for categories, tags, and search.

Sovereign, encrypted, persistent memory for AI agents. Eight MCP tools — remember, recall, forget (GDPR Art. 17 erasure), share, governance. Anchored on COTI V2 mainnet. Apache-2.0.

Strata is a native MCP server that gives agents verified intelligence across 22 AI ecosystems. Tools: * get_best_practices * get_latest_news * get_top_integrations * search_ecosystem * find_mcp_servers * Claude-validated content, injection-safe by design * Refreshed twice daily via automated pipeline * Works with Claude Code, Cursor, Windsurf, Cline * Free tier available Site: https://usestrat

A persistent semantic memory system for Claude Code that provides a structured, versioned document store with semantic search and graph visualization. It acts as a memoization layer to store and retrieve research, design decisions, and codebase insights across different work sessions.

An MCP server that ingests semiconductor PDFs into a Neo4j knowledge graph, enabling AI agents to query domain knowledge, verify claims against source text, and record design reasoning.