"Information about Jira" matching MCP servers:

MCP server that connects to Jira Data Center, enabling issue search, retrieval, creation, comments, workflow transitions, project listing, arbitrary JQL, and turning meeting notes into structured Jira stories, tasks, and bugs.

Enables read-only Jira Data Center insights by default, with opt-in audited write tools, sprint and release health summaries, and structured issue search via MCP.

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 Claude to read Jira CSV/JSON backlog exports, audit tickets for test readiness, and generate validated Gherkin acceptance scenarios tied to ticket criteria. It also tracks acceptance-criteria coverage and flags ambiguities or missing information for Product Owner follow-up.

Enables PM radar analysis of Jira projects, providing daily, sprint, and backlog reports with issue context and search.

A local MCP server for Jira Server/Data Center that enables Claude and Codex to manage issues, comments, transitions, worklogs, and links through the Jira REST API v2 using Basic Auth.

A Python MCP server that gives Claude access to PM workflow data such as sprints, roadmap, blockers, and workload, using synthetic fixture data (no API keys required) and can be forked for real Linear/Jira integration.

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.

Enables AI assistants to validate drafted user stories against INVEST and acceptance-criteria rules, suggest splits for oversized stories, and export finished backlogs to Markdown, CSV, or Jira CSV.

Enables AI agents to read-only access business intelligence in a Revinho workspace, combining Google Analytics 4, Stripe, and optionally Google Search Console to answer questions about changes, performance, revenue, underperformance, and opportunities.

Enables transforming grounded AI answers into interactive information views such as comparisons, plans, checklists, timelines, and decision views, while preserving a plain-language fallback.

Enables Claude Code to query a trained sentiment model and Amazon Electronics review analytics through typed, read-only tools. Supports sentiment classification, statistics, keyword and similar-review search, product summaries and comparisons, negative aspect analysis, and model information.

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 AI assistants to draft customer-ready or internal release notes from work closed in GitHub, Jira, or Linear, using deterministic fetching and rule-based categorization that flags uncertain items in a review list instead of guessing. Everything stays read-only, so a human approves and publishes the final notes.

An MCP server that connects Claude to the ProductBoard API v2, enabling natural language management of notes, entities, members, analytics, Jira integrations, and webhooks.

An MCP server that gives an agent product data, feedback, metrics, sandbox analysis, and gated Jira tickets — so it can investigate drops, write PRDs, and file work with evidence.

Provides a local, agent-maintained product context layer over MCP, serving structured strategy, competitor, customer feedback, and feature inventory data to any AI tool such as Claude, Cursor, or ChatGPT, with local data storage, bring-your-own-LLM support, and weekly evidence-based roadmap reviews that can sync suggestions to Jira or Linear.

MCP server that exposes project status tools (plan, milestones, RAID items, blockers) allowing AI assistants to retrieve and analyze project information via natural language.