AI powered Jira CLI and MCP server for humans and agents — manage issues, sprints, boards with interactive wizards, multi-provider AI
AI powered Jira CLI and MCP server for humans and agents — manage issues, sprints, boards with interactive wizards, multi-provider AI (OpenAI/Gemini/Anthropic), and an 14-tool MCP server for AI assistants. The jira pilot mcp server wraps that behind the Model Context Protocol, so an assistant can use it through 3 defined tools rather than through you.
jira-pilot is a next-generation CLI that combines traditional developer tools with modern AI capabilities.
Everything the assistant can do here goes through one of these:
Prerequisites — The Prerequisites tool exposed by this serverWorklogs — The Worklogs tool exposed by this serverSubtasks — The Subtasks tool exposed by this serverThe server ships on npm as @modelcontextprotocol/inspector, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Jira Pilot's toolset — Prerequisites, Worklogs, Subtasks — is a fair guide to whether it matches your workflow. It is maintained by aarul5; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Jira Pilot's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| Prerequisites | The Prerequisites tool exposed by this server. |
| Worklogs | The Worklogs tool exposed by this server. |
| Subtasks | The Subtasks tool exposed by this server. |
{
"mcpServers": {
"jira-pilot": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/inspector"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.