"Assistance with Java development" matching MCP servers:

Automates Java Maven testing workflows with decision table-based test generation, security vulnerability scanning, JaCoCo coverage analysis, and Git automation.

SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.

Local CI/CD engine for AI agents. ActionD listens to LGH git events and runs plugin jobs (Go/Python/Java/web toolchains) in isolated checkouts, with structured results, root-cause failure diagnosis, approval gates, and auto-rollback. The MCP server exposes 23 tools, including dev_cycle_run (commit → CI → structured verdict in one call) and actiond_diagnose for failed-job analysis.

Enables AI coding agents to orchestrate the full software development lifecycle on GitHub, including planning, issue creation, code review, security triage, and release readiness checks.

An MCP server that provides deterministic tools for AI assistants to standardize development workflows, including branch naming, commit validation, and PR checklists.

Enables Claude to run structured software development pipelines by directing it through sequential phases, validating evidence before advancing, and persisting state in SQLite for resumption across sessions.

A Model Context Protocol server that lets development agents work with Odoo.sh from their development environment, listing branches, watching builds, and streaming logs. It sits on top of the odouche Python library's public interface.

Enables CI/CD failure triage for GitHub Actions by inspecting failed runs, classifying root causes with LLM assistance, retrieving relevant runbook guidance, estimating flakiness, and either preparing dry-run fix PRs or publishing structured diagnoses to Discord for human review.

An MCP server designed for React Native and Expo development that provides specialized tools for project scaffolding, architectural best practices, and troubleshooting. It enables AI assistants to guide users through setup, navigation configuration, and CI/CD processes using modern stacks like NativeWind and Zustand.

An MCP server providing comprehensive Gitea API coverage with 186 tools for managing repositories, issues, pull requests, and CI/CD workflows. It enables autonomous AI agents to perform complex development and administrative tasks directly through a Gitea instance.

A Model Context Protocol (MCP) server for LocalStack that enables management of local AWS development environments, including container lifecycle operations, infrastructure deployments, log analysis with IAM policy generation, chaos injection, and Cloud Pods state management.

An MCP server that automates the full software development lifecycle through an AI-driven TDD state machine. It handles everything from task decomposition and test-driven development to integration testing and automated pull request creation.

Enforces disciplined programming practices by requiring AI assistants to audit their work and produce verified outputs at each phase of development, following structured workflows for refactoring, feature development, and testing.

Provides structured access to Xcode development tools including xcrun, xcodebuild, and xctrace for building, testing, and analyzing projects.

Enables Claude to interact with R package development workflows, including CRAN metadata lookup, dependency checking, testing, documentation validation, and release automation.

Provides structured project management through phase-based workflows, enabling planning, execution tracking, compliance checking, and automated documentation for software development projects.

A demonstration MCP server built with FastMCP v2.0 that provides basic mathematical calculations and greeting functionality. Features Docker containerization, comprehensive testing, and CI/CD automation for learning MCP development patterns.

Enables AI coding assistants to interact with JetBrains TeamCity CI/CD server through natural language commands. Supports triggering builds, monitoring status, analyzing test failures, and managing build configurations directly from development environments.

Integrates Honeybadger error tracking with Cursor IDE, allowing developers to fetch, analyze, and troubleshoot application errors directly from their development environment.

Enables monitoring and control of the SST development process by streaming dev logs, managing Lambda invocations, and executing lifecycle commands like start, stop, and restart. It provides real-time access to event streams and deployment status directly through the Model Context Protocol.