"Material Design Icons" matching MCP servers:

3D printing filament and materials knowledge MCP server. Gives LLMs authoritative access to 7,000+ filaments and curated material science knowledge.

MCP server that scrapes Terminal Trove to search CLI/TUI tools and retrieve design references like screenshots and install commands for agentic UI research.

Search URDB's product integrity database — integrity scores, enshittification events, warranty cuts, and material downgrades across consumer products. Sourced and evidence-backed.

Wraps the RASPA2 molecular simulation engine into MCP tools, enabling AI agents to autonomously design, validate, execute, and interpret molecular simulations for porous materials.

Provides AI assistants with access to materials science databases, enabling search and analysis of material properties, crystal structures, phase diagrams, and elastic properties through the Materials Project API.

MCP server giving AI models direct access to 30M+ resources at ETH Library Zurich – books, maps, images, archival material, and linked-data person records.

Ultra-lightweight MCP server for construction calculations and material estimation, enabling material calculator and cost estimator tools for structures like foundations, walls, slabs, and beams.

Calculates Human Design charts based on birth date, time, and location, providing type, strategy, authority, profile, gates, defined centers, and incarnation cross information.

Enables the creation and management of business design artifacts including Business Model Canvases, SWOT analyses, and user personas. It features project organization and AI-powered research tools to automatically populate frameworks with market data.

Exposes materials-science data, simulations, workflows, and computing capabilities to MCP hosts through a plugin-agnostic, contract-governed engine with progressive capability discovery, bounded context, scoped permissions, and provenance-traceable artifacts. Concrete integrations such as a real OPTIMADE provider plugin stay separately packaged, so servers remain focused and evidence-backed rather than unrestricted.

A virtual statistician MCP server that provides real statistical methods—design of experiments, hypothesis testing, regression, SPC, MSA—via tested Python libraries, with plain-language interpretations and plotted outputs.

MCP server for computational color science, offering 32 tools for spectral palette design, illuminant robustness certification, metamerism analysis, and color vision test generation.

Enables simulation and analysis of DeFi mechanisms, auctions, incentive compatibility, and governance attacks through a model context protocol interface.

MCP server that scans daily AI innovation sources (arXiv, Hacker News, GitHub) and normalizes discoveries into actionable Skill Sheets for domains like code, design, HR, agents.

Predictive supply-chain MCP server that forecasts material confirmation risks and enables AI clients to interact with the system via natural language.

Enables AI hosts to design and simulate complex adaptive systems, including managing agent types, running simulations, and analyzing emergent behavior, feedback loops, and sensitivities.

Enables natural language querying of OPTIMADE-compatible material databases like Materials Project and Materials Cloud via the Model Context Protocol. It provides tools for linting query filters, discovering database providers, and accessing full structured data results as MCP resources.

Enables retrieval of structured architectural case study data for design research, supporting case browsing, filtering, and downloadable research packages through natural language.

Cryptocurrency fundamental analysis tools via MCP. Enables users and AI agents to evaluate cryptocurrencies across 8 metrics using Sound Value principles. Provides educational material, fair value estimates, and valuation categories.

The Materials Project MCP Server is server that provides programmatic access to the Materials Project database. It enables LLMs, to search, analyze, and retrieve up to date materials science data.