"Amazon RDS" matching MCP servers:

Brings Redmine issue tracking into Claude Code with tools for reading, creating, and updating tickets, plus a /fix-bug skill for automated bug fixing.

Enables clients to retrieve structured work briefings and item details, analyze blockers, and submit next-action proposals through streamable HTTP tools backed by Amazon Bedrock conversations. Supports human-confirmed approval or cancellation while preserving revisions, decision histories, and safe reuse or invalidation of pending proposals.

Enables automated project analysis and structured development specification generation. Supports multiple export formats and integrates with AI models for comprehensive project documentation and validation.

An MCP server for RD Station CRM that enables managing contacts, deals, tasks and notes, and generating pipeline health reports through natural language in any MCP-compatible client like Claude.

Exposes Zentao REST API as MCP tools for listing/searching bugs, reading details with screenshots, and resolving bugs after explicit confirmation. Includes a setup wizard to configure Codex, Claude, Cursor and other clients.

Enables direct integration with Zentao bug tracking systems through Cursor. Supports authentication, bug retrieval, searching, and listing operations for comprehensive bug management through natural language.

Enables users to analyze, save, compare, and track bounty opportunities through a stateful MCP workflow, build submission plans, and request the next best action across sessions.

Enables local MCP clients to orchestrate a source-aware volunteer-briefing workflow with pause and takeover, incremental source checks, and exact-draft confirmation and download.

A self-hosted, Streamable HTTP MCP server that turns spoken end-of-day voice entries into a personal diary, extracting promises and to-dos with due dates from ordinary speech, merging near-duplicates, and prioritizing what matters most with explanations. It also lets users ask what's due, mark commitments complete by meaning, and receive pattern observations and reflections, using Amazon Bedrock for language understanding with an offline fallback.

Enables students to create and track study tasks, retrieve prioritized daily study plans, complete sessions, and monitor progress through MCP tools over Streamable HTTP.