"Element" matching MCP servers:

MCP server for Tru8 Evidence Research that enables AI agents to submit claims or URLs and receive source-traced evidence organized by tier and type with element decomposition and relationship mapping.

A Model Context Protocol server that distills documents from multiple sources into HTML articles and Obsidian notes, with features like key element detection, image filtering, and async task management.

yade-mcp connects AI agents to YADE — the open-source discrete element method engine — through the Model Context Protocol. Browse API docs, run simulations, and execute code, all through natural conversation.

The official MCP interface for AgentFEM, giving AI agents seven typed tools to create, validate, run, inspect, and verify finite-element simulations while preserving scientific evidence.

Enables AI tools to perform Chinese fortune-telling analysis including Ziwei Doushu (Purple Star Astrology) and Bazi (Four Pillars) chart generation, fortune reading, and element analysis. Supports multiple calendar systems and output formats for comprehensive divination services.

Enables AI-powered genomic variant analysis including variant impact prediction, regulatory element discovery, and batch variant scoring. Currently operates in mock mode as a proof-of-concept awaiting the public release of Google DeepMind's AlphaGenome API.

Enables AI assistants to drive Kratos Multiphysics finite element simulations end to end, including introspection, scaffolding, execution, and post-processing.

Provides access to the Korean elementary 2022 revised curriculum learning graph, enabling users to search and retrieve curriculum standards, learning topics, prerequisites, and roadmaps from a fully local database.

Enables traditional Chinese fortune-telling through BaZi (Four Pillars) analysis, including solar/lunar date conversion, Five Element balance calculations, Ten Gods deduction, and destiny interpretation for metaphysics applications.

MCP server for gene family analysis, providing tools for FASTA validation and PlantCARE cis-element prediction, with backend task management for AI agents.

Enables AI assistants to perform structural engineering analysis using the Pynite finite element library, including model creation, element definition, analysis execution, and result visualization through natural language.

Analyzes pommel horse gymnastics routines using a categorical aesthetics framework that evaluates element groups, spatial patterns, temporal qualities, and form with 85% deterministic taxonomy and 15% LLM synthesis.