"Information about systems" matching MCP servers:

Provides systems thinking models as composable analysis lenses for architecture, infrastructure, DevOps, incident analysis, and technical decision-making.

Generates engineer-grade SaaS specifications — design systems, database schemas, and RLS policies for AI build tools like Lovable, Cursor, and Claude Code. 4 tools, TypeScript, MIT licensed.

Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.

Enables AI assistants to understand and analyze Spring Boot codebases through static analysis, allowing natural language queries about endpoints, classes, dependencies, and architecture without running the application.

Enables AI agents to create, validate, and manage buildingSMART IDS (Information Delivery Specification) files with 100% compliance to the IDS 1.0 standard using IfcOpenShell's IfcTester library.

Semantic React/TSX analysis MCP server that saves 70-90% tokens by using AST to retrieve precise component usages, prop flow, and state update information for AI coding assistants.

An architecture consulting server that reviews multi-agent systems against a knowledge graph of patterns derived from expert literature. It provides grounded recommendations with chapter citations, maturity scoring, and interactive architecture diagrams to identify and fix structural gaps.

Enables analysis of KiCad electronic schematics through natural language queries to search components, trace signal paths, explore connections, and analyze multi-board systems.

Enables AI agents to programmatically create, modify, and analyze Draw.io diagrams through the Model Context Protocol. Supports generating architectural diagrams, flowcharts, and visualizations with bidirectional communication between AI systems and Draw.io.

12 deterministic graph-theory tools for structural analysis. Describe systems in EN syntax (subject do: action needs: inputs yields: outputs) — get topology, bottlenecks, blast radius, critical paths and lot more. No AI inside the computation.

MCP bridge to live SysML v1 models in CATIA Magic / Cameo Systems Modeler (No Magic MSoSA). Lets Claude Code or any MCP agent query, audit, and edit MBSE models — blocks, requirements, diagrams, parametrics, traceability — over a local, air-gapped connection.

Enables read-only access to Sparx Systems Enterprise Architect repositories stored in various database systems via ODBC, allowing AI assistants to browse and query model data without requiring Windows or a running EA instance.

Enables AI agents to query a repository's verified semantic model, including capabilities, ownership, contracts, constraints, impact, health, and verification status, without re-deriving project facts. It exposes read-only tools for inspecting, reasoning about, and verifying the provenance-tracked surface.

Provides access to a universal design token system with 7 pre-built themes (colors, typography, spacing, motion) and multi-format export capabilities for Canva, Remotion, PPTX, CSS, and W3C JSON.

Enables AI agents to architect and scaffold high-performance PostgreSQL-backed systems using the wpostgresql library, with tools for pattern search, connection validation, and project generation.

Generates editable Excalidraw diagram files from natural language descriptions of systems and architectures.

Enables coding agents to natively invoke Java project scaffolding operations such as initializing projects, adding modules, designing systems, and suggesting architectures.

Enables managing Cacoo diagrams, folders, organizations, and account information through MCP tools over HTTP, with OAuth-based authentication, email allowlisting, and support for multiple Cacoo accounts.

A public, read-only MCP server for researching Fermah products and documentation, with tools for searching docs, reading pages, listing products and proof systems, and generating non-binding project outlines.

Retrieves architectural information from ArchiMate models, enabling AI coding assistants to access architectural context during the software development lifecycle. Supports search and retrieval of views and elements in markdown, JSON, or YAML.