"How to create tasks or issues in Jira" matching MCP servers:

Enables LLMs to list, create, and comment on GitHub issues using your own GitHub identity via stdio transport.

Lets agents read a GitHub repository's live issues through read-only tools for listing, filtering, fetching details with comments and cross-references, searching, and exploring labels and milestones, with transparent pagination and provenance notes.

Enables triage of GitHub issues by fetching and filtering issues, checking claim status, and listing new open issues across a watch-list.

Enables AI agents to manage GitHub issues by listing, creating, searching, and commenting on them through MCP.

An MCP server that exposes outputty's task tracker as typed tools backed by GitHub Issues, allowing coding agents to manage tasks with two-way sync.

A standalone MCP server that exposes a narrow set of GitHub Issues tools for a single repository, securely handling a GitHub personal access token so agents never see the credential.

Exposes GitHub issue operations as tools for LLM agents, enabling listing, creating, commenting on, closing, and searching issues via natural language.

Enables AI assistants to discover, filter, and triage GitHub issues across repositories, with tools for fetching issue details, listing issues by state/labels, and finding related pull requests.

MCP server providing tools to read and write Jira Cloud issues, including a bridge to GitHub commits for tracing issues to code.

A Model Context Protocol (MCP) server for GitLab and Jira integration. This server allows AI agents like gemini-cli to interact with your GitLab and Jira instances.

Enables AI agents to interact with Jira and GitHub through MCP tools, including searching, creating, commenting on, and transitioning Jira issues and listing pull requests, summarizing diffs, creating issues, and commenting on GitHub.

Enables an AI coding agent to scan a day's git commits across work repositories and group them into Jira tickets, creating or updating them with estimates and logged time. It also surfaces actionable, categorized errors so an agent knows what failed and whether to retry.

A Scrum-aware MCP server that provides semantic analysis of Jira issues, sprint health, and Agile workflow intelligence, returning structured summaries and recommendations instead of raw Jira payloads.

Enables end-to-end automation of developer workflows from Jira issue tracking to GitHub pull requests through natural language, allowing developers to search issues, create branches, commit changes, and manage PRs directly from their IDE.

A Jira Server/Data Center MCP server for issue management, workflow analysis, and field discovery, using JQL and REST API v2 with PAT authentication.

Enables AI agents to manage self-hosted Atlassian Jira Server/Data Center issues and Bitbucket Server/Data Center repositories, pull requests, branches, commits, and files through MCP tools.

An MCP server for end-to-end Jira and GitHub integration, enabling AI agents in the IDE to automate workflows from issue tracking to pull request management.

An MCP server that enables AI agents to retrieve detailed GitHub Pull Request information using git commit hashes, branch names, or PR numbers. It automatically detects repositories and extracts comprehensive PR data including descriptions, labels, and reviews via the GitHub CLI.

A modular monolith MCP server connecting multiple providers (Redash, PostgreSQL, GitHub) with unified permission, security, and auditing, enabling secure data access and tool execution.

Enables seamless integration with GitLab and Jira Server/Data Center via MCP, using Bearer token authentication and REST API v2, supporting both on-premise instances.