mcp-dingding-bot
Enables sending markdown-formatted messages to DingDing/Dingtalk groups with support for custom titles and @all functionality
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-dingding-botsend a text message to the team: 'Daily standup in 5 minutes'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP DingDing Bot
MCP Server for the DingDing Bot API, enabling DingDing / Dingtalk message notifications and interactions.
Features
Message Notifications: Send various types of DingDing messages (text / markdown)
Related MCP server: dingtalk-mcp
Tools
send_text_messageSend a plain text message to a dingding group
Inputs:
text(string): Text contentatAll(optional boolean): Whether to @ all members
send_markdown_messageSend a markdown formatted message to a dingding group
Inputs:
title(string): Message titletext(string): Markdown contentatAll(optional boolean): Whether to @ all members
Setup
DingDing Bot Token
Create a DingDing group chat bot:
Go to group settings > Group Bot Management
Create a custom bot
Save the webhook URL and secret
Usage with Claude Desktop
Add the following to your claude_desktop_config.json:
Docker
{
"mcpServers": {
"gitlab": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e",
"DINGTALK_BOT_ACCESS_TOKEN",
"-e",
"DINGTALK_BOT_SECRET",
"shawyeok/mcp-dingding-bot"
],
"env": {
"DINGTALK_BOT_ACCESS_TOKEN": "<YOUR_ACCESS_TOKEN>",
"DINGTALK_BOT_SECRET": "<YOUR_SECRET>" // Optional, for robots with signature verification enabled
}
}
}
}NPX
{
"mcpServers": {
"gitlab": {
"command": "npx",
"args": [
"-y",
"mcp-dingding-bot"
],
"env": {
"DINGTALK_BOT_ACCESS_TOKEN": "<YOUR_ACCESS_TOKEN>",
"DINGTALK_BOT_SECRET": "<YOUR_SECRET>" // Optional, for robots with signature verification enabled
}
}
}
}Build
Docker build:
docker build -t shawyeok/mcp-dingding-bot .Environment Variables
DINGTALK_BOT_ACCESS_TOKEN: Your dingding group robot access token (required)DINGTALK_BOT_SECRET: Your dingding group robot signature secret (optional)
References
License
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
Available Tools
2 toolssend_markdown_messageC
Send a markdown message
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | The title of the message | |
| text | Yes | The text content to send | |
| atMobiles | No | The mobile numbers of users to @mention (ping) individually in the group chat | |
| atAll | No | Whether to @all the users in the group |
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. 'Send a markdown message' only indicates a sending action without revealing any behavioral traits such as permissions required, rate limits, whether it's a read-only or destructive operation, or what happens upon success/failure. This leaves critical behavioral aspects undocumented.
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 with just three words, making it front-loaded and free of unnecessary information. Every word directly relates to the tool's function, though this brevity comes at the cost of completeness. For conciseness alone, it scores perfectly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations, no output schema, and a sibling tool, the description is completely inadequate. It fails to explain what the tool does beyond its name, when to use it, behavioral aspects, or how it differs from 'send_text_message'. For a messaging tool with potential side effects and alternatives, this minimal description provides insufficient context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with all four parameters clearly documented in the schema itself. The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or usage examples. With high schema coverage, the baseline score of 3 is appropriate as the schema handles parameter documentation adequately.
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 'Send a markdown message' is a tautology that essentially restates the tool name 'send_markdown_message'. It doesn't specify what resource is being acted upon (e.g., a chat channel, notification system, or messaging platform) or distinguish this tool from its sibling 'send_text_message'. The purpose is vague and lacks specificity.
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?
There is no guidance on when to use this tool versus alternatives like 'send_text_message'. The description provides no context about appropriate use cases, prerequisites, or exclusions. Without any usage guidelines, agents cannot make informed decisions between similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_text_messageC
Send a plain text message
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text content to send | |
| atMobiles | No | The mobile numbers of users to @mention (ping) individually in the group chat | |
| atAll | No | Whether to @all the users in the group |
TDQS
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 but only states the basic action. It fails to mention critical aspects like required permissions, rate limits, side effects (e.g., message delivery confirmation), or error handling, which are essential for a messaging 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?
The description is a single, efficient sentence with zero wasted words. It is appropriately sized and front-loaded, clearly stating the core purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a messaging tool with no annotations or output schema, the description is insufficient. It lacks details on behavioral traits, response format, error conditions, and sibling differentiation, leaving significant gaps for agent understanding.
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 fully documents all parameters. The description adds no additional meaning beyond implying text content is sent, which the schema already covers. This meets the baseline for high schema coverage.
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 ('Send') and resource ('a plain text message'), making the purpose immediately understandable. However, it doesn't differentiate from its sibling 'send_markdown_message' beyond the format type, missing explicit comparison that would warrant a 5.
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 sibling 'send_markdown_message' or any alternatives. The description lacks context about appropriate use cases, prerequisites, or exclusions, leaving the agent without usage direction.
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. Dates show when Glama detected each change.
2 tool updates
v1.0.0- First observed
send_markdown_message - First observed
send_text_message
TDQS
The two tools have clearly distinct purposes: one sends markdown-formatted messages, and the other sends plain text messages. While both involve sending messages, the format distinction is explicit and unlikely to cause confusion, though they could be seen as overlapping in the broader 'send message' function.
Both tool names follow a consistent verb_noun pattern with 'send_' prefix and descriptive suffixes ('markdown_message', 'text_message'). The naming is predictable and adheres to a clear convention throughout the set.
With only 2 tools, the server feels thin for a bot that might handle more messaging operations (e.g., sending images, files, or managing conversations). This minimal set limits functionality and suggests an incomplete surface for a typical bot domain.
The tool set is severely incomplete for a Dingding bot domain. It only covers sending two message types, missing essential operations like receiving messages, managing users or groups, handling events, or supporting other media formats, which will likely cause agent failures in broader use cases.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
MCP server for GLM chat completions using Zhipu AI models via AceDataCloud
MCP server for Text-to-Speech
MCP server for AI dialogue using various LLM models via AceDataCloud
MCP server exposing the AceDataCloud Fish Audio API (text-to-speech with voice conditioning)
Related MCP Servers
- AlicenseNot gradedqualityCmaintenancedingding webhook mcp server24GPL 3.0
- -
- AlicenseBqualityCmaintenanceMCP Server for notify to telegram / weixin2129MIT
- AlicenseNot gradedqualityCmaintenanceA MCP server that exposes QQ bot capabilities over Streamable HTTP, enabling clients to query bot status, read group and friend info, fetch chat history, and send group/private text messages.2MIT
Appeared in Searches
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Shawyeok/mcp-dingding-bot'
If you have feedback or need assistance with the MCP directory API, please join our Discord server