"Jira" matching MCP servers:

Enables orchestrating Jira-driven software workflows by watching tickets, running herdr agents on active issues, and pushing updates to those agents over MCP.

Enables autonomous Jira-to-PR workflows in Claude Code by fetching context from Jira, GitHub, Notion, and Slack, building structured prompts, and handling branch pushes, PR creation, CI polling, and task completion.

Enables an event-driven operations agent to query internal SQL, GitHub, Slack, Jira, documentation, and Kubernetes telemetry through 28 RBAC-gated MCP tools, with shared memory for playbook retrieval and incident workflows.

Exposes AI agents as MCP tools to fetch Jira stories, generate BRDs and Playwright test scripts, run tests, and auto-heal broken locators. Integrates with Claude Desktop and Cursor IDE for enterprise-grade test automation.

Turns application errors into reviewed pull requests by automating root-cause analysis, Jira ticket creation, local and CI test gates, and GitHub PRs, with a human as the final merge gate.

Automatically provides AI agents with proven instructions and past failure warnings for common tasks like deployment, auth, and payments, enabling flawless execution without manual configuration.

An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.

Exposes a spec-compliant JSON-RPC 2.0 endpoint that lets external AI IDEs and agents query live Jira and Confluence context, traverse multi-hop dependency and policy graphs to simulate a release's blast radius, and mint tamper-evident SHA-256 Merkle release receipts. It also supports triggering autonomous remediation actions that create mitigation subtasks, alert affected downstream teams, and raise a ship-confidence score before deployment.

kira-mcp is a local MCP server that gives any MCP-compatible agent host full computer-use capabilities on the host machine, including screen perception with OmniParser and desktop automation.

Turns any AI coding agent or MCP client into a governed DevOps engineer by exposing policy-enforced tools for Kubernetes, Docker, Jira, Git/PR, CI/CD, AWS, Terraform, and incident response, with approvals, audit logging, secret redaction, and rollback enforced outside the model.

Enables AI assistants to analyze B2C Gold IRA sales call transcripts through 6 specialized prompts executed in strategic order. Provides structured analysis of conversation dynamics, psychology, objections, deal risk, and strategic qualification for retirement planning sales calls.

Routes a ticket to a specialised BA, developer, reviewer or refactor agent, gathering context from Jira, GitHub and SonarQube in parallel and producing a short implementation plan for the editor's model. Each run works in an isolated git worktree sandbox, follows the project's own rules files, and enforces command allowlists and secret-redacted audit logging.