"Information about computer usage" matching MCP servers:

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

Local-first MCP server for storing and managing project architecture, modules, data flow, and usage examples with complete privacy.

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.

Provides AI models with structured design guidelines and system prompts for creating consistent, high-quality interactive visualizations like charts, diagrams, and mockups. It enables on-demand loading of UI specifications to optimize token usage while ensuring visually polished and functional widget generation.

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.

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.

Builds a dependency and topology graph of a Kubernetes/FluxCD GitOps repository via static analysis, enabling AI agents to reason about service relationships without cluster access.

Enables AI agents to query Salesforce DX projects through MCP with compressed component specs, full-text search, dependency relations, annotations, and an interactive architecture map, drastically reducing token usage.

Provides precise AST-based code search and structural intelligence across Vue, Astro, and React/Next projects, including component usage audits, dependency trees, route scanning, state impact tracing, and dead component detection.

Multi-stack scaffolding engine for generating production-ready module structures (NestJS, Java Spring, Python FastAPI) directly from an MCP-compatible AI client, reducing token usage for boilerplate code.

Enables AI assistants to programmatically create and manage information flow diagrams — information items and information flows in StarUML.