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jira-mcp

by CamdenClark
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JIRA MCP 服务器

铁匠徽章

一个 MCP 服务器，支持大型语言模型 (LLM) 通过标准化工具和上下文与 JIRA 交互。此服务器提供使用 JQL 搜索问题以及检索问题详细信息的功能。

特征

  • JQL 搜索：执行复杂的 JQL 查询并支持分页

  • 问题详情：检索有关特定 JIRA 问题的详细信息

Related MCP server: JIRA MCP Server

先决条件

  • npm安装

  • 具有 API 访问权限的 JIRA 实例

  • JIRA API 令牌或个人访问令牌

  • 与 API 令牌关联的 JIRA 用户电子邮件

获取 JIRA API 凭证

  1. 通过https://id.atlassian.com登录您的 Atlassian 帐户

  2. 导航至安全设置

  3. 在 API 令牌下，选择“创建 API 令牌”

  4. 给你的令牌一个有意义的名字（例如，“MCP 服务器”）

  5. 复制生成的令牌 - 您将无法再次看到它！

  6. 使用此令牌作为您的JIRA_API_KEY

  7. 使用与您的 Atlassian 帐户关联的电子邮件地址作为JIRA_USER_EMAIL

用法

与 Claude Desktop 集成

  1. 将服务器配置添加到 Claude Desktop 的配置文件中：

macOS ： ~/Library/Application Support/Claude/claude_desktop_config.json Windows ： %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "jira": {
      "command": "npx",
      "args": ["-y", "jira-mcp"],
      "env": {
        "JIRA_INSTANCE_URL": "https://your-instance.atlassian.net",
        "JIRA_USER_EMAIL": "your-email@company.com",
        "JIRA_API_KEY": "your-api-token"
      }
    }
  }
}

  1. 重新启动 Claude Desktop 以加载新配置。

可用工具

1. JQL 搜索（ jql_search ）

使用可自定义参数执行 JQL 搜索查询。

参数：

  • jql （必需）：JQL 查询字符串

  • nextPageToken ：分页令牌

  • maxResults ：返回的最大结果数

  • fields ：要包含的字段名称数组

  • expand ：要包含的附加信息

例子：

{
  "jql": "project = 'MyProject' AND status = 'In Progress'",
  "maxResults": 10,
  "fields": ["summary", "status", "assignee"]
}

2. 获取问题（ get_issue ）

检索有关特定问题的详细信息。

参数：

  • issueIdOrKey （必需）：问题 ID 或密钥

  • fields ：要包含的字段名称数组

  • expand ：要包含的附加信息

  • properties ：要包含的属性数组

  • failFast ：是否在发生错误时快速失败

例子：

{
  "issueIdOrKey": "PROJ-123",
  "fields": ["summary", "description", "status"],
  "expand": "renderedFields,names"
}

发展

配置

在运行服务器之前设置环境变量。在根目录中创建一个.env文件：

JIRA_INSTANCE_URL=https://your-instance.atlassian.net
JIRA_USER_EMAIL=your-email@company.com
JIRA_API_KEY=your-api-token

将值替换为：

  • 您实际的 JIRA 实例 URL

  • 与您的 JIRA 帐户关联的电子邮件地址

  • 您的 JIRA API 令牌（可以在 Atlassian 帐户设置中生成）

安装

通过 Smithery 安装

要通过Smithery自动为 Claude Desktop 安装 JIRA：

npx -y @smithery/cli install jira-mcp --client claude

手动安装

  1. 克隆此存储库：

git clone <repository-url>
cd jira-mcp

  1. 安装依赖项：

npm install

使用 MCP Inspector 运行

对于测试和开发，您可以使用 MCP Inspector：

npm run inspect

添加新工具

要添加新工具，请修改index.js中的ListToolsRequestSchema处理程序：

server.setRequestHandler(ListToolsRequestSchema, async () => {
  return {
    tools: [
      // Existing tools...
      {
        name: "your_new_tool",
        description: "Description of your new tool",
        inputSchema: {
          // Define input schema...
        }
      }
    ]
  };
});

然后在CallToolRequestSchema处理程序中实现该工具。

执照

麻省理工学院

贡献

欢迎贡献！请随时提交 PR。

Available Tools

2 tools
get_issueC

Retrieve details about an issue by its ID or key.

ParametersJSON Schema
NameRequiredDescriptionDefault
issueIdOrKeyYesID or key of the issue
fieldsNoFields to include in the response
expandNoAdditional information to include in the response
propertiesNoProperties to include in the response
failFastNoFail quickly on errors

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves details, implying a read-only operation, but doesn't mention error handling (e.g., what happens if the ID/key is invalid), rate limits, authentication needs, or response format. This leaves significant gaps for an agent to understand how to use it effectively.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that efficiently conveys the core purpose without any unnecessary words. It's front-loaded and easy to parse, making it highly concise and well-structured for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what details are retrieved, how to handle optional parameters like 'fields' or 'expand', or what the response looks like. For a tool with multiple parameters and no structured output information, more context is needed to guide proper usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so parameters are well-documented in the schema itself. The description adds no additional meaning beyond implying retrieval by 'ID or key', which aligns with the 'issueIdOrKey' parameter but doesn't elaborate on usage. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Retrieve') and resource ('details about an issue'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from the sibling tool 'jql_search', which likely serves a different purpose (searching vs. retrieving by ID/key).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'jql_search'. It mentions retrieving by 'ID or key', which implies a specific use case, but doesn't clarify when to choose this over a search tool or address any prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updates
    • First observedget_issue
    • First observedjql_search
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TDQS

B3/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: get_issue retrieves a single issue by ID/key, while jql_search performs broader queries using JQL. There is no overlap or ambiguity between them, as they serve different use cases (specific lookup vs. flexible search).

Naming Consistency5/5

Both tools follow a consistent snake_case naming pattern with clear verb_noun structure: get_issue and jql_search. The naming is predictable and readable, with no deviations or mixed conventions.

Tool Count2/5

With only 2 tools, this server feels severely under-scoped for a Jira integration. A typical Jira MCP would need more operations like create_issue, update_issue, or list_projects to cover basic workflows. The current set is too thin for meaningful agent interaction.

Completeness2/5

The tool surface is significantly incomplete for Jira's domain. While get_issue and jql_search provide read/search capabilities, there are major gaps in CRUD operations (no create, update, or delete) and missing lifecycle management (e.g., transitions, comments). This will cause agent failures in common scenarios.

Maintenance

ActivityInactive
ResponsivenessNo issues

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