jira-mcp-ai
MCP server for Jira Cloud that lets AI agents search, read, and write Jira issues using your own Atlassian account and API token, with write operations gated behind explicit opt-in.
README
jira-mcp-ai
An MCP server for Jira Cloud: it gives an MCP-capable agent (Claude Code, Claude Desktop, or any other client) tools to search, read and — behind an explicit gate — write Jira issues, using your own Atlassian account and API token.
Two things shape the design:
- Writes are gated. Write tools default to describing what they would do
instead of doing it. Executing requires both an opt-in configuration and an
explicit flag on the call. See
docs/THREAT-MODEL.md. - Jira content is untrusted input. Issue text arrives from whoever filed the ticket. It is labelled as data, never merged into the agent's instructions.
Status: pre-code. The specification in
docs/is complete and normative; the implementation is being built against it. Nothing is published to npm yet, so the registration example below will not resolve until the first release.
Requirements
- Node.js ≥ 22 (env files are read with
process.loadEnvFile(), not dotenv) - A Jira Cloud site and an Atlassian API token
Registration
// .mcp.json / claude mcp add
{
"mcpServers": {
"jira": {
"command": "npx",
"args": ["-y", "jira-mcp-ai@0.1.0"],
"env": {
"JIRA_SITE": "mycompany",
"JIRA_EMAIL": "me@example.com",
"JIRA_API_TOKEN": "…",
"JIRA_WRITE_MODE": "plan"
}
}
}
}
The version is pinned on purpose: an unpinned npx -y re-resolves to whatever is
newest at spawn time, so a fresh publish could start running new code inside an
agent session with no review step. Bump the pin once you have read the changelog.
Configuration
Every setting is an environment variable with the JIRA_ prefix. The full table
— names, defaults, required-ness, and where credentials may live — is in
docs/CONFIGURATION.md; .env.example
is a fill-in-the-blanks copy.
Tools
<!-- GENERATED:TOOLS:START -->
The tool table is generated from the package definitions and inserted here.
Until then, docs/TOOLS.md is the catalog: tool names, input
and output shapes, packages, and the plan/apply contract for the write tier.
<!-- GENERATED:TOOLS:END -->
Data handling
What leaves your machine, what is written to disk, what is redacted from logs,
and what the write gate does and does not promise are documented in
docs/THREAT-MODEL.md. Credential storage and lifecycle
are in docs/AUTH.md.
To report a vulnerability, see SECURITY.md.
Development
npm install
npm run check # typecheck, lint, format, build, test, docs-lint, prod audit
docs/README.md is the index to the specification;
docs/ARCHITECTURE.md is the place to start.
Contributor conventions, the test taxonomy and the coverage gate are in
docs/TESTING.md.
License
MIT.
Jira and Atlassian are trademarks of Atlassian Pty Ltd. This project is an independent, unofficial client and is not affiliated with or endorsed by Atlassian.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。