"Information about Java" 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.

Pure Node.js MCP server that renders and validates PlantUML diagrams with zero Java and zero external server, powered by TeaVM. Exposes render_diagram, check_syntax and diagram_explain — just run npx @plantuml/mcp-js.

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.

Cross-repository code knowledge graph MCP server for Java, Kotlin, JavaScript, and TypeScript. Indexes source code into embedded KuzuDB via tree-sitter and exposes 30+ tools for call-flow tracing, multi-hop taint analysis (OWASP/CWE/PCI/STIG), entry-point reachability filtering, performance hotspot detection, and license compliance — without reading source files. 95% fewer tokens vs source-read

Enables inspection and analysis of project structures to detect languages, frameworks, entry points, and dependencies across multiple programming languages including Node.js, Python, PHP, Go, Java, and Rust.

AI-assisted COBOL to modern stack bridge that parses COBOL programs, maps to Python/Java/Go, generates test harnesses, and plans migration for legacy mainframe modernization.

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 scanning Java/Maven projects to generate TOGAF-standard architecture deliverables (Excel and PPTX) via natural language commands.

Analyzes Java Spring Boot Maven repositories by scanning source code, building a dependency graph, and exposing tools for architecture overview, change impact, dependency cycles, rule validation, and refactoring targets so LLMs can answer architecture questions without rereading the codebase.

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.

Generate UML class diagrams, sequence diagrams, flowcharts, and component diagrams from any Java or Spring Boot repository via CLI or directly inside Claude Desktop.

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

Enables analysis of Java call graphs in Axelor projects via ASM bytecode analysis, supporting dependency discovery, change impact analysis, and call chain tracing through SQLite queries.