Dida365(TickTick) API와 상호 작용하기 위한 도구를 제공하는 모델 컨텍스트 프로토콜(MCP) 서버입니다. AI 어시스턴트가 사용자 권한 부여 후 Dida365에서 작업과 프로젝트를 관리할 수 있도록 지원합니다.
Dida365를 통한 사용자 인증
모든 프로젝트(목록) 가져오기
수집 상자에서 작업 가져오기
다양한 매개변수로 새로운 작업 생성
수집 상자에서 기존 작업 업데이트
수집 상자에서 작업 삭제
새로운 프로젝트 만들기
Related MCP server: TickTick MCP
Node.js(v14 이상)
npm 또는 yarn
Dida365(틱틱) 계정
이 저장소를 복제하세요
종속성 설치:
지엑스피1
https://developer.dida365.com/manage를 열고 "새 앱"을 클릭하여 Dida365(TickTick) 앱을 만드세요.
"편집" 앱을 클릭하고 OAuth 리디렉션 URL " http://106.75.247.14:3999/oauth/callback "을 구성하세요.
클라이언트 ID와 클라이언트 비밀번호를 받으세요
" https://dida365.com/oauth/authorize?scope=tasks%3Aread%20tasks%3Awrite\&client\_id={client\_id}\&state=state\&redirect\_uri=http%3A%2F%2F106.75.247.14%3A3999%2Foauth%2Fcallback\&response\_type=code "를 엽니다.
{client_id}를 귀하의 client_id로 바꾸는 것을 잊지 마세요.
서버는 양식을 반환합니다.
클라이언트 ID와 클라이언트 비밀번호를 입력한 후 sumit을 입력하여 토큰을 받으세요.
커서를 열고 설정 > MCP로 이동하세요.
"새로운 글로벌 MCP 서버 추가"를 클릭하세요.
다음 구성을 mcp.json에 추가합니다.
"dida365": {
"command": "cmd",
"args": [
"/c",
"npx",
"-y",
"@smithery/cli@latest",
"run",
"@iamjzx/dida",
"--config",
"{\"token\":\"your token\"}"
]
}파일을 저장하고 mcp를 활성화합니다.
Claude Desktop을 열고 설정 > 개발자로 이동하세요.
개발자 모드 활성화
"구성 편집"을 클릭하여 claude_desktop_config.json을 엽니다.
"mcpServers" 섹션에 다음 구성을 추가합니다.
"dida365": {
"command": "cmd",
"args": [
"/c",
"npx",
"-y",
"@smithery/cli@latest",
"run",
"@iamjzx/dida",
"--config",
"{\"token\":\"your token\"}"
]
}파일을 저장하고 Claude Desktop을 다시 시작하세요.
src/server.log 파일에서 서비스 런타임 로그를 볼 수 있습니다.
API가 부족하여 다음 작업을 수행할 수 없습니다.
특정 프로젝트에서 작업 가져오기
특정 프로젝트의 기존 작업 업데이트
특정 프로젝트의 작업 삭제
특정 프로젝트에서 새 작업 만들기
ApiClient tool description
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | Message to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for disclosing behavioral traits. It fails to mention any side effects, authorization needs, rate limits, or return characteristics, offering only the generic name.
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 short but wastes its single sentence on a tautology. It is under-specified rather than concise, as it omits essential information that a longer description would provide.
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 generic name and the presence of siblings, the description is wholly incomplete. It does not mention the API being communicated with, the expected output, or any special behavior, rendering it insufficient for an agent to use correctly.
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 'message' is already documented in the input schema. The description adds no additional meaning or constraints 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 'ApiClient tool description' is a tautology that merely restates the tool name without specifying any verb, resource, or action. It does not distinguish this tool from siblings like 'data-processor' or 'file-handler'.
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 vs. alternatives. The description lacks any context, prerequisites, or examples, leaving the agent without any decision-making support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
DataProcessor tool description
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | Message to process |
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 tells nothing about side effects, permissions, restrictions, or return behavior, leaving the agent completely in the dark about what the tool does.
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 short (4 words) but wastes the opportunity to convey any useful information. Conciseness at the expense of substance is not valued.
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 low complexity (1 optional param, no annotations, no output schema), a minimal description should at least clarify the nature of processing. This description is completely inadequate.
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 'message' parameter has a description), so baseline is 3. The tool description adds no further meaning beyond the schema, but does not harm.
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 'DataProcessor tool description' is a tautology that merely restates the tool name without specifying any action or resource. It fails to convey what data processing actually entails.
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 versus its siblings (api-client, example_tool, file-handler, my-tool). There is no mention of context, prerequisites, or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
An example tool that processes messages
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | Message to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided and the description lacks any behavioral traits such as side effects, permissions, or read-only/mutating nature.
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?
While short, the description is under-specified and does not earn its place with substantive 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?
Given the simple schema and no output schema or annotations, the description fails to provide complete context, e.g., what the output is or expected 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 description coverage is 100%, so the description adds no value beyond the schema definition for the only parameter 'message'.
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 'processes messages' is vague and does not specify what kind of processing or distinguish from sibling tools like api-client, data-processor, and file-handler.
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 alternatives; no exclusions or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
FileHandler tool description
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | Message to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It contains no information about side effects, permissions, or any behavior beyond the name, leaving the agent completely uninformed.
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 very short, but it is underspecified rather than concise. It fails to convey useful information about the tool's purpose or usage, making it inefficient for an agent.
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 simplicity (single parameter, no output schema), the description should at least state what the tool does with the message. It does not, leaving the context completely incomplete.
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% (one parameter 'message' described as 'Message to process'). The description adds no additional meaning beyond the schema, so a baseline score 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 'FileHandler tool description' is a tautology, merely restating the tool name without specifying any verb or resource. It does not clarify what the tool does, and it fails to distinguish it from siblings like 'api-client' or 'data-processor'.
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, when not to, or how it compares to alternatives. The description is generic and offers no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
MyTool tool description
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | Message to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries full responsibility for behavioral disclosure. It merely repeats the tool name and offers no insight into side effects, permissions, 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?
While the description is short (three words), it is under-specified rather than concise. It lacks front-loaded key information and fails to earn its place by adding value.
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 single parameter, lack of output schema, and absent annotations, the description is grossly incomplete. It provides no operational context for agent invocation.
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%, and the input schema already describes the 'message' parameter. The description adds no further semantic value beyond the schema, so a baseline score 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 'MyTool tool description' is a tautology that restates the tool name without indicating any specific action or resource. It fails to distinguish from sibling tools like 'api-client' or 'data-processor'.
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 usage context or guidance is provided. The description does not specify when to use this tool over alternatives, nor does it mention 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.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
api-clientdata-processorexample_toolfile-handlermy-toolScored across 5 tools
The tool names are highly generic and vague, making it impossible to distinguish their purposes. Tools like 'api-client', 'data-processor', 'file-handler', and 'my-tool' could easily overlap in functionality, and 'example_tool' adds confusion without clear differentiation. This lack of specificity will likely cause agents to misselect tools due to ambiguous boundaries.
The naming conventions are inconsistent, mixing kebab-case (e.g., 'api-client'), snake_case (e.g., 'example_tool'), and camelCase (e.g., 'MyTool' in 'my-tool'). There is no predictable pattern in verb usage or structure, leading to a chaotic and unreadable set that lacks coherence.
With 5 tools, the count is reasonable for a server, but it feels borderline due to the vague and overlapping purposes. For a TickTick integration, this number might be thin if it aims to cover core task management features, but it's not extreme enough to score lower.
Given the server's name suggests a TickTick (Dida365) integration, the tool set is severely incomplete. There are no tools for core task management operations like creating, listing, updating, or deleting tasks, notes, or reminders. The generic tool names provide no coverage for the domain, leaving obvious gaps that will cause agent failures.
Manage tasks, Focus Zone, notes, projects, and task history from compatible AI assistants.
Task management for people and AI agents, with scoped OAuth access to issues, projects, and docs.
Task management for people and AI agents, with scoped OAuth access to issues, projects, and docs.
Create and manage MeisterTask projects, tasks, and notes from your AI assistant.
