"Kotlin RAG (Retrieval-Augmented Generation) implementation resources" matching MCP servers:

Provides LLM agents with a toolset for reviewing S1000D technical publications, including XML schema validation, cross-reference and applicability checks, skeleton generation, and AI-suggested fixes.

Provides aerodynamic analysis tools through MCP, enabling geometry generation, meshing, CFD solving, and visualization for 2D airfoils.

Enables AI assistants to interact with Yamcs mission control systems through natural language, providing tools and resources for telemetry, commands, links, storage, instances, and alarms.

Enables AI agents to drive SolidWorks for parametric modelling, aerospace part generation, sheet metal, weldments, assemblies, drawings, simulation, inspection, and file export. It provides approval-gated operations, verification tools, and journaling for safe, recoverable design automation.

Enables AI assistants to control and automate Abaqus/CAE simulations via MCP, including model query, job management, ODB inspection, KPI extraction, capsule tracking, physics contract validation, report generation, and viewport capture. It also supports noGUI batch mode, dual transport, and integration with Codex/Claude clients.

Enables retrieval of satellite vegetation statistics (NDVI) and searches of Sentinel-2 scene catalogs, returning results as JSON.

Enables satellite orbital mechanics calculations including visibility predictions, access window analysis, and TLE generation from natural language descriptions. Supports 200+ world cities and multiple orbit types (LEO, MEO, GEO, SSO, Molniya, Polar).