"Assistance with Java development" matching MCP servers:

A Jira-lite MCP server that enables planning-first workflows for AI-assisted development. It manages tickets as markdown files with YAML frontmatter, guiding agents through epics, stories, tasks, and architecture decision records.

Validates startup ideas with a deterministic scorecard, evidence brief, and verdict before code is written, integrating with MCP-aware build agents to avoid building dead-on-arrival products.

An AI-native product development pipeline that guides users from idea to shipping with structured research, architecture, build, validation, and traceability using 52 tools across 4 domains.

Enables reading and editing Avo tracking plans through natural language, with skills for designing new plans and working with existing ones.

A federated MCP server that combines IBM's engineering-ai-hub tools with its own authoring and orchestration tools for IBM ELM, enabling AI hosts to manage requirements, models, and compliance through a single interface.

Enables AI orchestrators to manage hierarchical implementation roadmaps with phases, tasks, and plan-change tracking.

Integrates with JetBrains YouTrack to enable issue tracking, project management, and user administration through natural language commands.

A production-ready MCP server enabling AI assistants to interact with Jira projects, issues, sprints, users, attachments, and worklogs via natural language, with support for both local stdio and remote HTTP transports, dual authentication methods, and enterprise-grade security controls.

Enables AI assistants to manage projects, tickets, tags, and relative weight prioritization calculations, with revision history and multi-project support.

Integrates with Aha.io product management platform, enabling offline data synchronization, semantic search, and workflow automation via natural language.

Headless MCP server for Simpson Strong-Tie product data. Provides AI agents with structural connector lookups, load calculations, code compliance verification, and engineering specifications.

A Model Context Protocol (MCP) server for Canny feedback management. Enables managing customer feedback, prioritizing features, and streamlining product development through natural language.

Connects Claude Code, Codex, Cursor, and other coding agents to a project's idea, feature topology, and ordered task queue over MCP, so they can answer planning jobs, claim, build, and tick off implementation tasks live in your repository, or assemble a shareable PRD.

Enables AI assistants to search, de-duplicate and route leads in a demo CRM, with read-only mode and an audit log for accountability.

Enables interaction with Posthog through a standardized MCP interface, providing access to Posthog's tools and services for analytics and product management.

Enables AI agents to interact with VoteShip feature requests, voting boards, roadmaps, and changelogs, including public board access without credentials and authenticated project administration with a project secret.

Enables AI agents to interact with Plane project management APIs, offering tools for managing projects, work items, cycles, modules, initiatives, and more through MCP.

Enables LLM clients to answer prospect questions about Timers Studio, a professional broadcast timer platform, with first-party data on competitive positioning, use cases, personas, and recommended plans.

Enables any MCP host to search and retrieve public job listings from yuancheng.work through the search_jobs and get_job tools, with read-only access and soft location filtering.

Exposes MCP tools over Streamable HTTP that turn ranked Sygnal signals into voice-ready buyer-intent briefings with analyst verdicts, card and carousel payloads, and session state for a simulated Alexa+ experience. It also surfaces the next recommended action so a voice assistant can guide users through follow-ups, with fallback fixtures when the live signal feed is restricted.