# jira-mcp

> jira-mcp — softspark-jira-mcp. Use this tool when you need to integrate AI clients with multiple Jira instances, enabling them to read, update, and comment on tasks with formatted output and efficient caching. It solves problems of fragmented task management and limited AI access to Jira data, providing a unified interface for AI agents like Claude. With inputs from Jira instances and outputs in ADF format, use jira-mcp to streamline AI-driven task management across disparate systems.

Canonical page: https://skillsregistry.net/skills/softspark-jira-mcp  
JSON: https://api.skillsregistry.net/v1/skills/softspark-jira-mcp

## Description

Model Context Protocol server for Jira - lets Claude and other AI clients read, update, and comment on tasks across multiple Jira instances, with ADF formatting and local caching

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** productivity
- **Updated:** 2026-09-24

## Source

- **Source listing:** [GitHub](https://github.com/softspark/jira-mcp)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "softspark-jira-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/softspark-jira-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/softspark-jira-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt