Claude Code DingTalk MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: configure webhook settings, notify session end with stats, and send three different message types (link, markdown, text). There is no overlap in functionality, making tool selection straightforward for an agent.
Naming Consistency5/5All tools follow a consistent 'dingtalk_verb_noun' pattern with snake_case throughout. The naming is predictable and readable, with no deviations in style or convention.
Tool Count5/5With 5 tools, the server is well-scoped for its purpose of DingTalk integration. Each tool serves a specific function (configuration, notifications, messaging), and none feel redundant or missing for the apparent scope.
Completeness4/5The toolset covers core messaging and notification workflows for DingTalk, including configuration and different message formats. A minor gap might be the lack of tools for reading or managing incoming messages, but the surface is largely complete for sending notifications and messages.
Average 2.9/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'configure' which implies a write/mutation operation, but doesn't specify whether this is a one-time setup, overwrites existing settings, requires authentication, or has side effects like rate limits. This is a significant gap for a tool that likely modifies system state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a configuration tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., idempotency, permissions), expected outcomes, or error handling, which are crucial for an agent to use it correctly in context with sibling notification tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters (webhook, secret, keywords) with their types and optionality. The description adds no additional meaning beyond what the schema provides, such as example values or usage context, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('configure') and resource ('DingTalk webhook settings'), making the purpose understandable. However, it doesn't differentiate this configuration tool from the sibling notification tools (dingtalk_notify_session_end, dingtalk_send_link, etc.), which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 doesn't mention prerequisites (e.g., needing a DingTalk account), exclusions, or how it relates to the sibling tools for sending notifications, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Send') but doesn't mention whether this requires authentication, has rate limits, affects group state, or what happens on success/failure. For a messaging tool with zero annotation coverage, this leaves critical behavioral traits unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a messaging tool with no annotations and no output schema, the description is insufficient. It doesn't cover behavioral aspects like authentication needs, error handling, or response format, and it fails to differentiate from sibling tools, leaving gaps in contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters (title, text, messageUrl, picUrl) with clear descriptions. The description adds no additional meaning beyond implying these parameters are used to construct a 'link message,' which is minimal value over what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Send') and target ('link message to DingTalk group'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like dingtalk_send_markdown or dingtalk_send_text, which presumably also send messages to DingTalk groups but in different formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 dingtalk_send_markdown or dingtalk_send_text. It mentions 'link message' but doesn't explain what contexts or message types warrant a link format over text or markdown, leaving the agent to guess based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('send') but doesn't cover critical aspects like whether this requires specific permissions, rate limits, error handling, or what happens on success/failure. For a messaging tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy to parse quickly while conveying the essential action and target.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a messaging tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, dependencies on other tools like 'dingtalk_configure', or how it fits into the broader DingTalk ecosystem. This leaves the agent with incomplete context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-specific information beyond what's already in the schema, which has 100% coverage with clear descriptions for 'title', 'text', and 'atAll'. Since the schema fully documents the parameters, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract from the schema's completeness.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('send') and resource ('markdown message to DingTalk group'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'dingtalk_send_text' or 'dingtalk_send_link' which also send messages, leaving room for ambiguity about when to choose markdown format over text or link formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'dingtalk_send_text' or 'dingtalk_send_link'. It lacks context about prerequisites (e.g., authentication setup via 'dingtalk_configure'), target audience, or scenarios where markdown is preferred over plain text or links.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions sending a message but doesn't cover critical aspects like authentication requirements, rate limits, error conditions, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple tool and front-loads the core functionality without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, error handling, or behavioral traits like side effects. Given the complexity of sending messages (which involves authentication and potential failures), more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('content' and 'atAll') adequately. The description doesn't add any parameter-specific information beyond what's in the schema, such as content length limits or '@all' behavior details, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('send a text message') and target ('to DingTalk group'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'dingtalk_send_markdown' or 'dingtalk_send_link' that also send messages, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'dingtalk_send_markdown' or 'dingtalk_send_link', nor does it mention prerequisites or context for sending messages. It simply states what the tool does without usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'automatic stats' which hints at some automated behavior, but doesn't clarify what these stats include, how the notification is formatted, whether it requires specific permissions, or any rate limits. This leaves significant gaps for a tool that presumably sends external notifications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Send a session completion notification') and adds a key feature ('with automatic stats'). There's zero waste or redundancy, making it appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters with full schema coverage but no annotations or output schema, the description is minimally adequate. It identifies the tool's purpose but lacks details on behavioral traits, error handling, or output expectations. For a notification-sending tool, more context on delivery mechanism or response format would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds no additional parameter semantics beyond implying that parameters like 'duration' and 'mainTasks' feed into 'automatic stats'. This meets the baseline of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Send a session completion notification') and the resource ('with automatic stats'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like dingtalk_send_text or dingtalk_send_markdown, which might also send notifications but with different content formats or purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage at the end of a session ('session completion notification'), but provides no explicit guidance on when to use this tool versus alternatives like dingtalk_send_text for general messages. There's no mention of prerequisites, exclusions, or comparative context with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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