planka-mcp
planka-mcp
通过 15 个 MCP 工具,从 Claude Code 控制 Planka 2.x 看板。 写入操作会被重新读取并验证,因此报告的成功与看板实际状态一致。 一个可选工作流可将该看板转化为代理工作的持久记忆。
You talk to Claude Code
│
▼
planka-mcp (stdio) ─── HTTPS + JSON ───▶ Planka 2.x
│ │
└──── reads the result back ◀──────┘[!WARNING] 旧的
@gogogadgetbytes/planka-mcp包可能在 Planka 2.x 上报告成功,但实际上 什么都没做。在替换现有安装之前,请先阅读四个静默失败陷阱。
刚接触 MCP?请先阅读本节
MCP 是一种标准,它允许 Claude Code 调用由另一个程序提供的工具。
本仓库运行一个本地小程序,将这些工具调用转换为 Planka API 请求。
它需要 Planka 凭据,因为它以专用 Planka 用户的身份运行,而不是以 Claude 本身的身份。
凭据保留在您的机器上,绝不会写入项目级的 .mcp.json 文件。
Claude Code 在会话启动时加载 MCP 服务器,因此在设置或配置更改后请重启它。
Related MCP server: kanban-mcp
要求
Node.js 18 或更高版本以及
npm一个可访问的 Planka 2.x 实例
一个可以看到目标项目和看板的专用 Planka 用户
已安装并可作为
claude使用的 Claude Code仅当设置需要创建看板时,才需要项目管理员角色
支持 Linux 和 macOS。不需要 Bun 运行时。
5 分钟安装
克隆仓库并运行引导式安装程序:
git clone https://github.com/omnicoreos/planka-mcp.git
cd planka-mcp
./scripts/setup.sh设置过程会询问 Planka URL、代理邮箱或用户名以及密码。它会在写入配置之前 验证这些凭据,让您选择或创建看板,然后运行一次真实的创建/标签/评论/删除冒烟测试。
它提供两种 Claude Code 配置:
选项 | 使用场景 | 存放位置 |
| 您想要最简单的个人设置 | Claude Code 用户配置 |
项目 | 团队应共享服务器条目 |
|
在两种情况下,设置都会将凭据存储在 Git 之外的
~/.config/planka-mcp/config.json 中,权限为 0600,并创建私有启动器
~/.local/bin/planka-mcp。生成的团队配置不包含密码:
{
"mcpServers": {
"planka": {
"type": "stdio",
"command": "${HOME}/.local/bin/planka-mcp",
"args": []
}
}
}安装程序可以安全地重新运行。它会更新 planka 条目,复用现有的
工作流列表和标签,并删除其临时冒烟测试卡片。
验证是否正常工作
首先,检查 Claude Code 的配置:
claude mcp list
claude mcp get planka然后完全重启 Claude Code。如果您选择了 .mcp.json,请在该
项目中打开 Claude Code,并在提示时批准项目级服务器。
向 Claude Code 提问:
Show me my Planka projects and boards. In the Pending list, create a card named
"MCP is working" with the description "Created from Claude Code", then read it back.如果 Claude 看不到这些工具,请先重启,然后按照 故障排除 进行操作。
15 个工具
ID 是字符串。从 planka_get_structure 开始,然后使用 Planka
返回的 ID;不要猜测它们。
工具 | 功能 |
| 列出可见的项目、看板和列表 |
| 读取一个看板及其列表、卡片、标签,以及可选的任务计数 |
| 创建卡片,并可附加任务和标签 |
| 读取完整的卡片详情 |
| 更新标题、描述、截止日期或完成状态 |
| 将卡片移动到另一个列表或位置 |
| 永久删除卡片 |
| 向卡片添加清单任务 |
| 重命名或完成任务 |
| 删除任务 |
| 创建、更新或删除看板标签 |
| 添加或移除标签,并验证最终状态 |
| 通过 Planka 2.x 的专用端点添加评论 |
| 通过专用端点读取评论 |
| 创建、更新或删除看板列表 |
每个工具的每个输入字段和完整负载都位于 工具参考 中。
可选代理工作流
MCP 服务器可以独立工作。可选方法解决的是另一个问题: 在代理会话之间保留工作存在的原因、发生的变化以及仍然成立的事实。
分层采用:
仅使用 MCP 工具。
添加看板状态、卡片模板和人工握手。
为每张卡片添加一个工作树,由主管协调工作进程。
从一个能跨越会话存活的看板开始。 看板模板、可复制的 Claude Code 技能 以及可选的 工作树辅助工具 都是独立的组件。
故障排除
报告错误时,请包含 Planka 版本、Node 版本、工具名称 和错误文本。切勿粘贴凭据或访问令牌。
致谢与许可证
这是
gogogadgetbytes/planka-mcp
的 MIT 许可分支,而非从零开始的原创实现。有关
上游归属、维护的修复和未答复的拉取请求,请参阅 CREDITS.md。
有关原始和当前贡献者声明,请参阅 LICENSE。
开发
npm ci
npm run build
npm test真实的冒烟测试是可选加入的,因为它会修改一个可写看板,然后自行清理:
export PLANKA_BASE_URL="https://planka.example.com"
export PLANKA_AGENT_EMAIL="agent@example.com"
export PLANKA_AGENT_PASSWORD="<YOUR_PASSWORD>"
export PLANKA_SMOKE_BOARD_ID="1234567890123456789"
npm run test:smoke在提交更改之前,请参阅 CONTRIBUTING.md。发布身份
集中在 project.identity.json 中;在您自己的命名空间下发布之前,
请更新它并运行 npm run sync:identity。
Available Tools
15 toolsplanka_add_commentA
Add a comment to a card. Use this for status updates, notes, or agent activity logs.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Comment text (markdown supported) | |
| cardId | Yes | The card ID |
TDQS
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 indicates a mutation ('Add') but does not mention permissions, idempotency, side effects, or what the response contains. This is a significant gap for a write operation with zero annotation coverage.
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?
Two short sentences convey the action and use cases without any wasted words. The core purpose is front-loaded, making it easy for an agent to parse quickly.
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?
For a simple two-parameter tool with no nested objects and no output schema, the definition gives enough context to invoke it correctly. It does not describe return values or side effects, but the use-case framing and schema coverage make the tool's operation reasonably complete.
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 both parameters are already documented in the input schema. The description adds no extra parameter-level detail, but the baseline of 3 applies because the schema handles the parameter semantics sufficiently.
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 opens with a specific verb-resource pairing: 'Add a comment to a card.' This clearly identifies the action and target, and naturally distinguishes it from sibling tools like planka_get_comments and planka_set_card_labels.
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 phrase 'Use this for status updates, notes, or agent activity logs' gives practical context for when to invoke the tool. It does not explicitly name alternatives or exclusions, but the intended use cases are clear enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_create_cardA
Create a new card on a board. Optionally add tasks (checklist items) at the same time.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Card title | |
| tasks | No | Optional: Task names to add as a checklist | |
| listId | Yes | The list to create the card in | |
| dueDate | No | Due date in ISO format | |
| labelIds | No | Optional: Label IDs to attach | |
| description | No | Card description (markdown supported) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states the action and optional task inclusion, without mentioning side effects, idempotency, permissions, or error handling. As a mutating operation, more transparency is expected to prevent misuse.
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, efficient sentence with no fluff. The primary action is front-loaded, and the optional task feature is stated secondary. It is easily scannable and to the point.
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?
For a create tool with full schema coverage, the description is minimal but sufficient for basic invocation. However, it does not reference the sibling tool planka_create_tasks, which could lead to misuse when adding tasks to an existing card. Additionally, no return value or post-creation behavior is mentioned, though no output schema exists to fill that gap.
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?
The input schema already provides complete descriptions for all six parameters, so the baseline is 3. The description adds no extra parameter insight beyond restating that tasks are checklist items, which the schema already mentions. Therefore, it does not enhance parameter understanding.
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 'Create a new card on a board' with a specific verb and resource. It also mentions the optional task functionality, distinguishing it from tools like planka_create_tasks. This makes the purpose unambiguous and distinct from sibling operations.
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 usage context is implied: you use this tool to create a card. However, there is no explicit guidance on when to use alternatives like planka_create_tasks for adding tasks later, nor any exclusions or conditions. The phrase 'at the same time' hints at a timing option but does not clarify the separation of concerns.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_create_tasksA
Add one or more tasks (checklist items) to a card.
| Name | Required | Description | Default |
|---|---|---|---|
| tasks | Yes | Task names to create | |
| cardId | Yes | The card ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It states the mutation ('Add') but does not disclose what happens to existing tasks, whether the operation is idempotent, what response is returned, or any authorization requirements. This is a significant gap for a mutation tool.
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?
One sentence, no filler, with the action and target front-loaded. Every word earns its place.
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?
For a simple, two-parameter tool with a fully described schema, the description plus schema is largely sufficient for invocation. It does not cover behavioral edge cases like duplicate task names or whether an existing checklist is appended to, but the low complexity makes this minor.
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 cardId and tasks. The description only reinforces 'one or more' and 'to a card' without adding syntax, format, or relationship details, which matches the baseline 3.
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?
States a specific verb ('Add'), resource ('tasks'), and clarifies they are checklist items attached to a card. This distinguishes it from sibling tools like create_card or update_task, so an agent can identify the operation immediately.
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 implies when to use the tool—when adding one or more checklist tasks to a card—but gives no explicit guidance about alternatives or exclusion criteria. It does not mention update_task/delete_task or clarify prerequisites such as card existence.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_delete_cardA
Permanently delete a card. This cannot be undone.
| Name | Required | Description | Default |
|---|---|---|---|
| cardId | Yes | The card ID to delete |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden and it does disclose the most critical trait: the delete is permanent and cannot be undone. This is exactly what an agent needs before invoking a destructive tool; it stops short of describing cascading effects or response shape.
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?
Two short sentences with zero filler. The core action is front-loaded ('Permanently delete a card') and the irreversibility warning earns its place.
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?
For a one-parameter tool this is close to sufficient, but with no annotations and no output schema the description still leaves unspecified whether deleting a card also deletes its tasks/comments and what the caller can expect in the response. The irreversibility warning mitigates but does not fully close this gap.
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?
There is only one parameter and schema description coverage is 100%, so the schema already defines cardId as 'the card ID to delete.' The description adds no extra semantic detail, but none is necessary at this complexity.
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 names a specific verb ('delete') and resource ('card') and adds the permanence qualifier, so an agent can distinguish it from get_card, update_card, move_card, and create_card. No tautology or ambiguity.
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 intended use is implied: choose this when a card should be permanently removed. However, it does not explicitly state when not to use it or compare it to alternatives, and it gives no preconditions beyond selecting a cardId.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_delete_taskA
Delete a task from a card.
| Name | Required | Description | Default |
|---|---|---|---|
| taskId | Yes | The task ID to delete |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must itself convey side effects. It only says 'delete', which implies removal but does not explicitly state irreversibility or any potential cascading effects. This is a minor gap for a destructive operation, so a score of 3 is appropriate.
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, straightforward sentence without redundant information. It is concise and to the point.
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?
For a simple delete operation with one parameter and no output schema, the description covers the essential context. It does not mention preconditions (e.g., task must exist) but that is generally implied and not critical for such a simple operation.
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?
The only parameter 'taskId' is described as 'The task ID to delete', which fully explains its purpose and type. No further elaboration is needed.
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 'delete' and the resource 'task', making the purpose unambiguous. It distinguishes the tool from sibling tools like 'planka_delete_card' without needing further clarification.
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 specifies the action and resource, which is sufficient for a delete operation. It does not explicitly compare with alternatives, but given the tool name and sibling context, usage is clear. It could have added a note about when to use it versus other task-related tools, but that is not necessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_get_boardA
Get a board with all its lists, cards, and labels. Use this to see everything on a board.
| Name | Required | Description | Default |
|---|---|---|---|
| boardId | Yes | The board ID | |
| includeTaskCounts | No | Include task completion counts for each card |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must carry the behavioral burden. It indicates a read-only operation via 'Get' and states what is returned, but it does not disclose any further behavioral details such as response structure or how includeTaskCounts affects results.
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?
Two short sentences, front-loaded with the operation and scope. The second sentence adds a clear usage instruction without redundancy, so every sentence earns its place.
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?
For a simple board-fetching tool with one required parameter and one documented optional parameter, the description is sufficient. It states what is returned, and the schema covers parameter semantics. No output schema exists, but the description compensates by naming the returned content.
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 parameter meanings are already documented. The description adds no extra meaning beyond the schema, meeting the baseline for a fully documented schema.
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 states a specific verb ('Get') and a specific resource ('a board') with an explicit scope: all its lists, cards, and labels. This clearly distinguishes it from narrower siblings like get_card or get_comments.
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?
It gives clear usage context: use this when you want to see everything on a board. It does not explicitly list alternatives or exclusion cases, but the intended use is obvious and unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_get_cardA
Get full details of a card including tasks, comments, labels, and attachments.
| Name | Required | Description | Default |
|---|---|---|---|
| cardId | Yes | The card ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. 'Get' clearly signals a read-only operation, and the description discloses what content is returned. It does not cover auth requirements, cost, or rate limits, but for a simple fetch tool this is a reasonable baseline.
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?
A single sentence that front-loads the verb and resource, then enumerates the included content without filler. Every word earns its place.
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?
For a one-parameter read tool with full schema coverage and no output schema, the description is largely sufficient — an agent needs only cardId to invoke it correctly. It could name sibling tools for routing, but nothing essential is missing for a correct call.
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% — cardId is already described as 'The card ID'. The description adds no further meaning about parameter format, how to obtain the ID, or expected values, which matches the baseline for fully documented schemas.
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?
States a specific verb (Get), resource (card), and the content scope (tasks, comments, labels, attachments). The listed contents implicitly distinguish it from planka_get_comments (scoped to comments only), though this differentiation is implied rather than explicit.
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?
Usage context is implied through the listed content — an agent can infer that retrieves the full card payload versus sibling tools like planka_get_comments or planka_get_structure. However, there is no explicit when-to-use or when-not-to-use statement, nor mention of alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_get_commentsA
Get all comments on a card.
| Name | Required | Description | Default |
|---|---|---|---|
| cardId | Yes | The card ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the scope ('all comments') and implies a read-only operation via 'Get', but it does not mention any behavioral traits such as ordering, limits, or the shape of returned data. This is adequate for a simple retrieval but adds minimal context.
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, concise sentence with no unnecessary words. It is front-loaded with the core action and resource, making it immediately scannable.
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?
For a simple get operation with one required parameter and no output schema, the description is complete. It states the resource ('comments on a card') and implies the need for a card ID. Nothing an agent needs to call this tool correctly is missing.
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?
The schema description coverage is 100% with a clear description for cardId. The tool description does not add any additional meaning beyond what the schema already provides, so the baseline of 3 is appropriate.
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 'Get all comments on a card' clearly states the specific action (get) and resource (comments on a card), making it distinct from sibling tools like planka_add_comment or planka_get_card. The scope is unambiguous.
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 is provided on when to use this tool over alternatives. It does not name any sibling tools or describe contexts where another tool might be more appropriate. Usage is only implied by the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_get_structureA
Get the full project/board/list structure. Use this to understand what projects and boards exist before working with cards.
| Name | Required | Description | Default |
|---|---|---|---|
| projectId | No | Optional: Get structure for a specific project only |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. 'Get' clearly frames this as a read operation)Skip, which is adequate. However, it doesn't state anything explicit about side effects (there are none expected), data size, or whether the response nests cards. For a pure retrieval tool that is evidently read-only, this is acceptable but not exemplary.
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?
Two sentences, front-loaded with the primary purpose. Every sentence earns its place — the first states the action, the second gives usage intent. No filler or repetition.
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?
For a simple tool (1 optional param, no output schema), the description covers what it returns (full project/board/list structure) and when to use it (before working with cards). It might briefly mention how this relates to planka_get_board, but for a discovery tool this is largely sufficient.
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% — the projectId parameter is fully described in the schema ('Optional: Get structure for a specific project only'). The description itself adds no parameter-level meaning beyond what the schema already provides, so the baseline of 3 is appropriate.
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?
States a specific verb ('Get') plus a concrete resource ('full project/board/list structure') and names the navigation intent. It is clearly distinct from siblings like planka_get_board or planka_get_card, which retrieve narrower targets.
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?
Explicitly instructs when to use it: 'before working with cards' to discover what projects/boards exist. It doesn't spell out when not to use it or how it compares to planka_get_board (which is a sibling), so it misses a small exclusion note, but the primary use case is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_manage_labelsB
Create, update, or delete labels on a board.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Label name | |
| color | No | Label color. Valid colors: muddy-grey, autumn-leafs, fresh-salad, lilac-eyes, silver-glint, deep-ocean, summer-sky, grey-stone, sugar-plum, shady-rust, wet-rock, turquoise-sea, lavender-fields, french-coast, sweet-lilac, pirate-gold, berry-red, pumpkin-orange, lagoon-blue, pink-tulip, light-mud, orange-peel, bright-moss, antique-blue, dark-granite, lagune-blue, sunny-grass, morning-sky, light-orange, midnight-blue, tank-green, gun-metal, wet-moss, red-burgundy, light-concrete, apricot-red, desert-sand, navy-blue, egg-yellow, coral-green, light-cocoa, modern-green, piggy-red | |
| action | Yes | Action to perform | |
| boardId | No | Board ID (required for create) | |
| labelId | No | Label ID (required for update/delete) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears the full burden of behavioral disclosure. It only states the action types without explaining that the action parameter determines which IDs are required (boardId for create, labelId for update/delete), that delete is permanent, or any side effects. The description adds no behavioral context beyond the literal action words.
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, concise sentence with no verbose filler. It front-loads the core verb and resource. While some might argue it is too terse for full completeness, the conciseness itself is exemplary; no words are wasted.
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's complexity—five parameters, an enum action, and conditional required fields—the description is far from complete. It does not explain how the action parameter drives the input requirements, nor does it mention return values or any usage context. An agent would need to inspect the schema carefully to understand the conditional logic, which a well-formed description should preempt.
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 baseline is 3. The description itself does not elaborate on any parameter semantics—it merely repeats the action types. The conditional requirements (e.g., boardId for create, labelId for update/delete) are already encoded in the schema's descriptions, so the description adds no additional value beyond the schema.
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 states a specific verb-resource combination: 'Create, update, or delete labels on a board.' It covers all three CRUD actions and clearly distinguishes from sibling tool planka_set_card_labels, which handles assigning labels to cards rather than managing label definitions. This is precise and immediately scopes the tool.
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 explicit guidance on when to use this tool versus alternatives is provided. It does not mention that this is for managing label metadata (e.g., names, colors) as opposed to assigning labels to cards, nor does it reference any sibling tool. The agent is left to infer context from the name alone, which is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_manage_listsA
Create, update, or delete lists on a board.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | List name | |
| type | No | List type. Defaults to active when creating. | |
| action | Yes | Action to perform | |
| listId | No | List ID (required for update/delete) | |
| boardId | No | Board ID (required for create) | |
| position | No | List position |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. However, it only restates the action verbs already present in the schema enum and does not disclose side effects, irreversibility, permissions, or what happens to cards/tasks when a list is deleted.
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, front-loaded sentence. Every word contributes: the verbs identify the operations and 'lists on a board' identifies the target resource.
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?
The input schema is complete and the description is clear enough for basic use. However, there is no output schema, no annotations, and no mention of what the tool returns, how errors surface, or the consequences of each action, so the context is only minimally sufficient.
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 all parameters are already documented in the schema. The description adds no parameter-level meaning, which matches the baseline for a schema that covers every parameter.
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?
It names the primary operations (create, update, delete) and the specific resource (lists on a board). Among the siblings, only planka_manage_labels is similarly phrased but for a different resource, so this tool is clearly differentiated.
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 phrase 'lists on a board' makes it clear when this tool applies: for list lifecycle operations. It does not explicitly name an alternative or state exclusions, but there is no sibling dedicated to lists, so the usage context is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_move_cardA
Move a card to a different list or position. Use this for workflow transitions (e.g., 'To Do' -> 'In Progress').
| Name | Required | Description | Default |
|---|---|---|---|
| cardId | Yes | The card ID | |
| listId | Yes | Target list ID | |
| position | No | Position in the list (lower = higher). Default: end of list |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly indicates a mutation action ('Move') and hints at the effect on card state (changing list/position). It doesn't disclose possible side effects like sorting behavior or potential errors, but the main behavioral trait (moving between lists) is transparent. The example also gives a practical cue.
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?
Two sentences with no waste. The core purpose is front-loaded, and the example is a single parenthetical. It's appropriately sized for a tool with three parameters.
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's complexity (3 params, no output schema, no annotations), the description covers the essential context: what it does, when to use it, and the position parameter semantics. It lacks explicit mention of return behavior (e.g., returns updated card or success message), but for a move action, that may not be critical. The sibling list provides navigation context.
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 the schema already describes all three parameters. The description adds the workflow context and clarifies that position is optional (default end). However, it doesn't add detail beyond the schema's own descriptions, but since the schema is complete, the baseline is 3, and the description's example slightly elevates it.
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 ('Move a card to a different list or position') with specific verbs and resources, and immediately distinguishes it from sibling tools like planka_update_card (which updates card fields) and planka_create_card. The example workflow ('To Do' -> 'In Progress') makes the purpose concrete.
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 explicitly states when to use this tool: for workflow transitions. It doesn't explicitly mention alternatives or exclusions, but the sibling list makes the context clear. Since it's a specific move action, the usage context is fairly self-evident, but it could have noted that this is distinct from updating card fields (planka_update_card).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_set_card_labelsA
Add or remove labels from a card. Pass label IDs from the board (planka_get_board lists them), not label names. Reports what actually landed on the card, verified by re-reading it.
| Name | Required | Description | Default |
|---|---|---|---|
| cardId | Yes | The card ID | |
| labelIds | No | Alias of addLabelIds. Label IDs to add. | |
| addLabelIds | No | Label IDs to add. Alias: `labelIds` (both are accepted and merged). | |
| removeLabelIds | No | Label IDs to remove |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full behavioral burden. It discloses a notable behavior: 'Reports what actually landed on the card, verified by re-reading it,' revealing a post-operation verification step. Yet it does not mention whether the change is idempotent, how errors on invalid label IDs are handled, or whether it merges or replaces the label set—though the schema's add/remove semantics imply merging. Thus it is partially transparent but incomplete.
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 extremely concise and well-structured: two short sentences that front-load the core action, then provide a key input caveat, and finally disclose the verification behavior. Every sentence earns its place, with no filler or repetition of schema details.
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?
For a tool with 4 parameters (one required), no output schema, and no annotations, the description covers the essential aspects: purpose, input source for IDs, and post-action verification. It omits edge cases like error handling or behavior when no labels are specified, and it does not explicitly state the return value, but the verification note implies a response. Given the tool's moderate complexity, this is reasonably complete.
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 all parameters are documented. The description adds valuable semantic guidance beyond the schema by directing the agent to use label IDs from planka_get_board rather than names, and by implicitly clarifying the behavior of addLabelIds vs removeLabelIds through the description's 'add or remove' phrasing. This compensates for any potential ambiguity about the alias relationship, which is already in the schema.
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 opens with a clear verb and resource ('Add or remove labels from a card') and adds crucial specificity by instructing to pass label IDs from the board rather than names, referencing planka_get_board. This differentiates it from sibling tools like planka_manage_labels, which likely handles label definitions, by focusing on card-level assignment.
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 gives an explicit operational guideline: 'Pass label IDs from the board (planka_get_board lists them), not label names.' This tells the agent exactly what input to fetch and how to structure the call. However, it does not explicitly state when to prefer this tool over alternatives such as planka_manage_labels, leaving some comparison implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_update_cardB
Update a card's properties (name, description, due date, completion status).
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | New card title | |
| cardId | Yes | The card ID | |
| dueDate | No | New due date (null to clear) | |
| description | No | New description (null to clear) | |
| isCompleted | No | Mark card as complete/incomplete |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It implies a mutation operation (update) but doesn't state whether it's destructive, if it requires specific permissions, or if it partially updates only provided fields. The description adds a hint of safety by implying it's a targeted update, but there's no explicit disclosure of side effects.
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, concise sentence that front-loads the primary purpose and lists the key fields. It's efficient and easy to parse, with no redundant information.
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?
The tool has 5 parameters, a simple schema, and no output schema, which reduces complexity. The description covers the core action and fields but doesn't explain partial update behavior or return values, which could be useful. Given the simplicity, the description is mostly complete but could be slightly richer with usage context.
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 the schema already documents all parameters. The description re-lists some fields (name, description, due date) but doesn't add new meaning like behavior when parameters are omitted or how null values clear fields. The schema's descriptions already cover these semantics, so the description adds minimal value beyond the baseline.
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 tool updates a card's properties and lists specific fields (name, description, due date, completion status), distinguishing it from sibling tools like create_card or move_card. It is specific enough for an agent to understand the resource and action, though it doesn't name a sibling to differentiate from.
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 implies this tool is for modifying existing cards, which is clear from the context. However, it doesn't provide explicit guidance on when to use this versus alternatives like planka_create_card or planka_move_card, nor does it mention any prerequisites (e.g., card must exist). This is adequate but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
planka_update_taskB
Update a task's name or completion status.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | New task name | |
| taskId | Yes | The task ID | |
| isCompleted | No | Mark as complete/incomplete |
TDQS
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 indicates a mutation but does not explain side effects, whether omitted fields are preserved, permission requirements, or what the response contains.
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 with no filler, and the core action and affected fields are front-loaded. It is concise and easy to parse.
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?
For a simple 3-parameter update tool, the description plus fully documented schema is minimally viable, but it lacks usage guidance and behavioral context such as partial update behavior or return value. No output schema or annotations exist to compensate.
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%, with each parameter already described ('New task name', 'The task ID', 'Mark as complete/incomplete'). The description adds little beyond mapping 'completion status' to isCompleted, so the baseline of 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?
The description uses a specific verb ('Update') and resource ('a task'), and names the exact fields affected ('name or completion status'). This clearly distinguishes it from sibling tools like planka_create_tasks and planka_delete_task.
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 gives no guidance on when to choose this tool over alternatives such as planka_create_tasks or planka_update_card, and no exclusions or prerequisites are stated. Usage is only implied by the word 'update'.
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.
15 tool updates
v0.1.0- First observed
planka_add_comment - First observed
planka_create_card - First observed
planka_create_tasks - First observed
planka_delete_card - First observed
planka_delete_task - First observed
planka_get_board - First observed
planka_get_card - First observed
planka_get_comments - First observed
planka_get_structure - First observed
planka_manage_labels - First observed
planka_manage_lists - First observed
planka_move_card - First observed
planka_set_card_labels - First observed
planka_update_card - First observed
planka_update_task
TDQS
Scored across 15 tools
Most tools have clearly distinct resource-action pairs, but planka_get_structure and planka_get_board overlap in what they return, and manage_lists/manage_labels bundle multiple operations while set_card_labels is narrow. Overall, the descriptions resolve most ambiguity.
The planka_ prefix and snake_case verb_noun pattern are consistent and readable. The use of 'manage' for lists and labels is a slight deviation from the more specific create/update/delete verbs, but not confusing.
15 tools is at the upper edge of the ideal range but each tool represents a distinct operation needed for board, card, task, label, and comment management. No tool feels redundant.
The toolkit covers the core lifecycle for cards, tasks, labels, and lists, plus comments and board structure reading. Missing comment update/delete and board-level CRUD are minor gaps that agents can work around.
Maintenance
Related MCP Connectors
Task & board management for AI agents + humans. Kanban, comments, digests via MCP.
AI-native Kanban board — connect Claude to claim, work and move your tasks over MCP.
Remote MCP for Kanban AI boards—manage projects, tasks, and comments from AI tools.
Persistent AI memory shared across Claude, ChatGPT, coding agents, and compatible MCP clients.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceEnables AI-powered project management by connecting Claude to Planka kanban boards via 75+ MCP tools for creating, updating, and managing projects, boards, lists, and cards.1GPL 3.0
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to manage Planka kanban boards, including creating, updating, and organizing tasks, lists, and cards via MCP.22 npm60MIT
- AlicenseNot gradedqualityBmaintenanceEnables users to interact with Planka (a Trello-like kanban tool) through natural language, using their own Planka access tokens for authentication and permissions. Supports remote hosting via HTTP, allowing multi-user MCP access to boards, lists, cards, and more.22 npmMIT
- FlicenseCqualityAmaintenanceEnables AI assistants to manage Planka projects, boards, lists, cards, tasks, labels, comments, stopwatches, and memberships through MCP tools.56-