GitHub Kanban MCP Server
🎯 GitHub Kanban MCP 服务器
📋 概述
GitHub Kanban MCP Server 是一个模型上下文协议 (MCP) 服务器,用于以看板格式管理 GitHub 问题并简化 LLM 任务管理。
Related MCP server: GitHub MCP Server
🚀 功能
🔄 以看板格式管理 GitHub 问题
🤖 使用 LLM 进行自动化任务管理
📊 可视化项目进度
🔗 与 GitHub 完全集成
💬 任务评论
📁 项目结构
kanban-server/
├── src/ # ソースコードディレクトリ
│ ├── handlers/ # リクエストハンドラー
│ │ ├── comment-handlers.ts # コメント関連の処理
│ │ ├── issue-handlers.ts # Issue関連の処理
│ │ ├── label-handlers.ts # ラベル関連の処理
│ │ └── tool-handlers.ts # ツールリクエストの処理
│ ├── schemas/ # 入力スキーマ定義
│ │ ├── comment-schemas.ts # コメント関連のスキーマ
│ │ └── issue-schemas.ts # Issue関連のスキーマ
│ ├── utils/ # ユーティリティ関数
│ │ ├── error-handler.ts # エラー処理
│ │ └── exec.ts # コマンド実行関連
│ ├── server.ts # MCPサーバーの実装
│ └── types.ts # 型定義
├── docs/ # ドキュメント
│ └── v0.2.0/ # バージョン別ドキュメント
└── assets/ # アセットファイル🛠️ 安装
先决条件
Node.js 18.x 或更高版本
npm 9.x 或更高版本
GitHub CLI(gh)
# パッケージのインストール
npm install @sunwood-ai-labs/github-kanban-mcp-server
# GitHub CLIの認証設定
gh auth login⚙️ 设置
将以下内容添加到您的 MCP 配置文件中:
{
"mcpServers": {
"github-kanban": {
"command": "github-kanban-mcp-server"
}
}
}🔧 可用工具
1. 列出问题
获取看板上的问题列表。
输入参数:
repo:GitHub 存储库名称(必填)state:问题的状态(“打开”,“关闭”,“全部”)。labels:要过滤的标签数组。
2. 创建问题
创建新问题。
输入参数:
repo:GitHub 存储库名称(必填)title:问题标题(必填)emoji:在标题开头添加的表情符号body:问题的主体labels:标签数组assignees:要分配的用户数组
3. 更新问题
更新现有问题。
输入参数:
repo:GitHub 存储库名称(必填)issue_number:发行号(必填)title:新标题emoji:在标题开头添加的表情符号body:新身体state:新状态(“打开”,“关闭”)。labels:新标签数组assignees:新任务的数组
4. 添加评论
为任务添加评论。
输入参数:
repo:GitHub 存储库名称(必填)issue_number:任务(问题)的 ID(必需)body:评论内容(支持Markdown格式)(必填)state:评论时要更改的问题状态('打开','关闭')
📝 许可证
MIT 许可证 - 请参阅LICENSE文件。
🤝 贡献
Fork此存储库
创建功能分支(
git checkout -b feature/amazing-feature)提交您的更改(
git commit -m '✨ feat: 素晴らしい機能を追加')推送到分支(
git push origin feature/amazing-feature)创建拉取请求
📮 反馈
如果您有任何问题或建议,请创建问题。
Available Tools
4 toolsadd_commentB
タスクにコメントを追加
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | コメントの内容(Markdown形式対応) | |
| repo | Yes | GitHubリポジトリ名 | |
| state | No | コメント時に変更するissueの状態(オプション) | |
| issue_number | Yes | タスク(Issue)のID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description is too brief. It does not mention that the state parameter can modify the issue state, nor any side effects like notifications. The description fails to compensate for the absence of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but lacks structure and additional detail. It does not fully earn its place as the sole explanation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters, no output schema, and no annotations, the description is insufficient. It omits important context such as the return value, the effect of the optional state parameter, and that it operates on GitHub issues.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents all parameters. The description adds no additional semantic context beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (add a comment) and resource (task/issue), distinguishing it from sibling tools like create_issue which creates new issues.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 update_issue. It lacks context for appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_issueC
新しいissueを作成します
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | issueの本文(## の先頭には絵文字を付与して可読性を上げて) | |
| path | No | Gitリポジトリの絶対パス | |
| emoji | No | タイトルの先頭に付与するユニークな絵文字 | |
| title | Yes | issueのタイトル | |
| labels | No | issueのラベル | |
| assignees | No | アサインするユーザー |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided and description gives no behavioral details (e.g., permissions, side effects, return value).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise and direct. Could include more context but no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema and description omits return type, success/error behavior, or any important constraints beyond the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameter descriptions exist. The tool description adds no extra meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description '新しいissueを作成します' clearly states it creates a new issue. This distinguishes it from siblings (add_comment, list_issues, update_issue).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. Does not mention any prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_issuesC
カンバンボードのissue一覧を取得します
| Name | Required | Description | Default |
|---|---|---|---|
| path | No | Gitリポジトリの絶対パス | |
| state | No | issueの状態 | |
| labels | No | フィルタリングするラベル |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states it retrieves a list, but does not disclose behavioral traits such as whether it is read-only (implied but not explicit), pagination, ordering, or any side effects. The description is insufficient for an agent to understand side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is to the point and front-loaded with the action. It is concise and contains no filler. However, it could benefit from additional context while remaining efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and no annotations, the description is too minimal. It does not explain the output format or behavior (e.g., whether it returns all issues or paginated). The mention of Kanban board adds some context, but overall it lacks completeness for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the three parameters clearly. The tool description adds no additional meaning beyond the schema, meeting the baseline. It does not compensate for any gaps, but none exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb '取得する' (get) and resource 'issue一覧' (list of issues) in the context of 'カンバンボード' (Kanban board). It distinguishes from sibling tools (add_comment, create_issue, update_issue) which are mutating. However, it does not explicitly state that it is read-only or mention filtering capabilities beyond the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It does not specify prerequisites, scenarios, or explicitly exclude other tools. Siblings are mentioned in context signals but not referenced in the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_issueC
既存のissueを更新します
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | 新しい本文 | |
| path | No | Gitリポジトリの絶対パス | |
| emoji | No | タイトルの先頭に付与する絵文字 | |
| state | No | 新しい状態 | |
| title | No | 新しいタイトル | |
| labels | No | 新しいラベル | |
| assignees | No | 新しいアサイン | |
| issue_number | Yes | issue番号 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description offers no behavioral details such as whether fields are overwritten or merged, idempotency, or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence but under-specified for a tool with 8 parameters; lacks necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, no output schema, no annotations), the description is completely inadequate, failing to explain update semantics or return behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 8 parameters, so the description adds no further value; baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description is a tautology: '既存のissueを更新します' simply restates the tool name without specifying what aspects can be updated or any unique behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings (add_comment, create_issue, list_issues). No mention of prerequisites or context.
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.
4 tool updates
v1.0.0- First observed
add_comment - First observed
create_issue - First observed
list_issues - First observed
update_issue
TDQS
Scored across 4 tools
Each tool targets a distinct operation: listing, creating, updating, or commenting on issues. No two tools overlap in purpose, so an agent can clearly distinguish them.
All tool names follow a consistent snake_case verb_noun pattern (list_issues, create_issue, update_issue, add_comment). The verbs are clear and predictable.
With 4 tools, the server is tightly scoped to core Kanban board operations. Every tool serves a necessary function without redundancy or bloat.
The basic lifecycle of issues is covered (list, create, update, comment). Missing operations like deleting or archiving issues are a minor gap since GitHub issues are typically closed rather than deleted, but board-specific transitions are not explicitly exposed.
Maintenance
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