AgilePlace MCP Server
agileplaceMCP_v3
AgilePlace 데모 프로비저닝 MCP 서버. Claude Desktop 또는 Cursor에서 데모 환경(보드, 대량 카드, 계층 구조)을 생성하고 구성합니다. stdio 전송 방식, 단일 사용자.
Module | 역할 |
| 환경 변수 기반 설정 + 인증된 HTTP 클라이언트(Bearer). |
| 첫 사용 시 보드 목록 워밍; 보드별 카드 유형 지연 로딩; 라벨 → ID 해석. |
|
|
| 대량 카드 생성. |
| stdio MCP 진입점. |
createCards
순차적이고 자체 조절되는 쓰기.
호출당 최대 ~40개 카드; 더 큰 배치는 거부됨(분할 후 재시도).
카드별
clientKey상관관계, 결과에 반영.오류 처리: 재시도(429 / 5xx / 네트워크), 카드 실패-계속(400 / 422 / 404), 배치 중단(401 / 403), 반복되는 동일 실패 시 서킷 브레이커.
부분 성공 시
isError: false반환;created[]에 있는 카드는 재제출하지 않아야 합니다.
Related MCP server: @nightsquawktech/gohighlevel-mcp-server
Configuration (Configuration을 유지할까? 문서 구조를 보면 heading text는 translate하라고 했으니...)
Hmm, actually the instruction says "Translate prose only" - but headings are prose? Wait: "Translate prose only. Keep the following verbatim..." - keeping technical terms verbatim. Headings like "Configuration", "Status", "createCards" - "createCards" is a function/tool name, keep verbatim. "Configuration" and "Status" are normal English words, so they should be translated.
Yes, I translate the heading text:
Configuration → ## 설정
Status → ## 상태
createCards → keep as createCards? Hmm, yes since it's a tool name. Even though it's a heading, the content "createCards" is a function name. Keep verbatim.
Actually wait - looking at the structure, "## createCards" is a section heading. The term "createCards" is a tool name. It should stay verbatim per the rules.
Let me also handle "Run standalone:" - "단독 실행:" Works.
GXP1 and GXP2 are placeholders - keep as is. Actually, looking at the structure, GXP1 is on its own line, and GXP2 on its own too. These look like placeholder tokens. Keep them.
Let me finalize.# agileplaceMCP_v3
AgilePlace 데모 프로비저닝 MCP 서버. Claude Desktop 또는 Cursor에서 데모 환경(보드, 대량 카드, 계층 구조)을 생성하고 구성합니다. stdio 전송 방식, 단일 사용자.
Module | 역할 |
| 환경 변수 기반 설정 + 인증된 HTTP 클라이언트(Bearer). |
| 첫 사용 시 보드 목록 워밍; 보드별 카드 유형 지연 로딩; 라벨 → ID 해석. |
|
|
| 대량 카드 생성. |
| stdio MCP 진입점. |
createCards
순차적, 자체 조절 쓰기.
호출당 최대 ~40개 카드; 더 큰 배치는 거부됨(분할 후 재시도).
카드별
clientKey상관관계, 결과에 에코.오류 처리: 재시도(429 / 5xx / 네트워크), 카드 실패-계속(400 / 422 / 404), 배치 중단(401 / 403), 반복되는 동일 실패 시 서킷 브레이커.
부분 성공 시
isError: false반환;created[]의 카드는 재제출하지 않아야 합니다.
Configuration
자격 증명은 소스가 아닌 호스트 구성의 env 블록(claude_desktop_config.json 또는 Cursor mcp.json)에 설정합니다.
{
"mcpServers": {
"agileplace-v3": {
"command": "node",
"args": ["/absolute/path/to/src/server.mjs"],
"env": {
"AGILEPLACE_DEFAULT_URL": "https://<your-org>.leankit.com/io",
"AGILEPLACE_DEFAULT_TOKEN": "<token>"
}
}
}
}단독 실행:
node src/server.mjs상태
createCards— 구현됨.updateCards/findCards/createBoard— 아직 미구현.보류됨: 다중 환경 라우팅, 레인 이름 해석, OKR 도구, 전체 호출 멱등성, 작업 확장.
Available Tools
1 toolcreateCardsCreate CardsA
Bulk-creates cards on one board. Use for new cards, not updates. Returns created[] with clientKey + the real id for a later connect pass; failed[] carries clientKey + title + reason. Pass type as a label ("Epic"); the tool resolves it. header is cosmetic and is not used to connect cards. One board per call. Max 40 cards per call — chunk larger sets and concatenate created[] before connecting. Partial success is normal: isError: false with some cards in failed[]. Cards in created[] already exist — NEVER resubmit those clientKeys. To complete a partial batch, resubmit only the failed[] (and any never-sent) cards. This applies to every partial result, not just retryAfter rate-limit cases. If retryAfter is set, wait that many seconds, then resubmit only the never-sent cards (not created[]). Never invent board, type, or lane ids. Attach to an existing parent with parentCards; otherwise create all cards first, then connect using the returned ids.
| Name | Required | Description | Default |
|---|---|---|---|
| cards | Yes | Cards to create. Max 40 per call; chunk larger sets. | |
| boardId | Yes | Target board title or id. One board per call. |
Output Schema
| Name | Required | Description |
|---|---|---|
| failed | Yes | |
| created | Yes | |
| summary | Yes | |
| retryAfter | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes far beyond annotations. The description discloses partial success semantics (isError: false with failed[]), idempotency implications (created[] cards already exist), the tool's resolution of type labels, the cosmetic nature of header, and explicit prohibitions like 'Never invent board, type, or lane ids.' These behaviors are not inferable from annotations alone.
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 long and dense, but each sentence provides essential operational detail for handling partial failures, rate limits, and parent-card connections. It is front-loaded with the core purpose and then systematically covers edge cases. Slightly more structured formatting (bullets) could improve readability, but nothing is wasteful.
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 (bulk creation, partial success, retryAfter, parent linkage) and the presence of an output schema, the description is exceptionally complete. It explains return values, error handling, chunking, idempotency rules, and integration steps, leaving no significant ambiguity for an AI agent.
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?
Although the schema already describes all parameters (100% coverage), the description enriches meaning by clarifying usage: 'type' is resolved to typeId, 'header' is cosmetic and not used for connections, 'clientKey' is echoed in responses, and 'boardId' accepts title or id. These are practical semantics that go beyond mere field descriptions.
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 'Bulk-creates cards on one board,' a specific verb+resource statement that clearly identifies the tool's function. It also explicitly distinguishes from updates ('Use for new cards, not updates'), which helps differentiate even in the absence of sibling tools.
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?
Provides explicit guidance on when to use the tool ('Use for new cards, not updates') and how to handle failures ('resubmit only the failed[] cards'). It covers chunking (>40), partial success, retryAfter logic, and never resubmitting created[] clientKeys, giving clear directives for safe and correct usage.
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 tool update
v3.0.0- First observed
createCards
TDQS
Scored across 1 tool
Only one tool exists, so there is no possibility of overlap or misselection. Its purpose is explicit: bulk-create cards on a board.
The single tool uses a clear verb_noun camelCase name, createCards, but there is no broader naming pattern to evaluate consistency across a set.
For an AgilePlace server, one tool covering only card creation is too narrow; agents will likely need other board, lane, and card lifecycle operations. The tool itself is substantial, but the server is under-scoped.
Only creation is exposed; there are no read, update, delete, search, or connect operations for cards or boards. Bulk creation is handled robustly, but most AgilePlace workflows hit dead ends.
Maintenance
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