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., "@chathook 帮我写一封邮件，然后询问是否需要修改"
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.
在 AI 完成任务后弹出原生输入对话框，让用户直接输入回复，保持对话不中断，直到用户明确结束。
用户提问 → AI 处理任务 → AI 调用 chat_hook 工具
↓
弹出原生桌面对话框（输入框 + 提交按钮 + 倒计时）
↓
用户输入回复 / 关闭对话框结束
↓
工具返回用户输入 → AI 继续处理
↓
AI 再次调用 chat_hook ...
↓
用户关闭对话框 → 工具返回结束信号
↓
AI 结束回合，对话完成Related MCP server: mcp-interactive-ui-server
在 MCP 客户端的配置中添加：
{
"mcpServers": {
"chathook": {
"command": "npx",
"args": ["-y", "mcp-chathook"]
}
}
}{
"mcpServers": {
"chathook": {
"command": "npx",
"args": ["-y", "github:kedaya2025/mcp-chathook"]
}
}
}git clone https://github.com/kedaya2025/mcp-chathook.git
cd mcp-chathook
npm install
npm run build{
"mcpServers": {
"chathook": {
"command": "node",
"args": ["<path-to>/mcp-chathook/dist/index.js"]
}
}
}在 AI Agent 的系统提示词 / 自定义指令中添加：
所有对话或任务结束时，都必须调用 chathook 工具来向用户确认工作进程，
除非用户结束该工具的调用视为任务完成不再调用。MIT
Display an input dialog to the user and wait for their response.
IMPORTANT: After completing a task or response, you SHOULD call this tool to ask the user if they need anything else. This keeps the conversation alive without requiring the user to type a new message.
The tool will block until the user responds. Possible return values:
Normal text: The user's new request or feedback. Continue working.
[CHATHOOK:USER_DECLINED]: The user clicked 'Decline' (end conversation). Stop calling this tool and end your response.
[CHATHOOK:USER_CANCELLED]: The user cancelled the input. You may end your response or call this tool again.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | The message to display to the user. This should include a summary of what you've done and a prompt for what they'd like next. | |
| suggestions | No | Optional quick-reply buttons. e.g. ['继续', '修改上面的内容', '结束对话']. The user can still type freely if they prefer. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses that the tool blocks until user response. It lists three return value types with clear instructions on how to interpret each, covering both normal and special cases.
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 concise and well-structured: first sentence states purpose, then an important usage note, then blocking behavior and return values. Every sentence is meaningful and front-loaded.
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, the description covers all necessary aspects: purpose, usage, blocking behavior, return values, and parameter usage. No output schema is needed as return values are explained.
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 baseline is 3. The description adds context beyond schema: the message should include a summary and prompt, and suggestions are for quick-reply buttons. This enhances understanding of how to use parameters effectively.
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's purpose: 'Display an input dialog to the user and wait for their response.' It also specifies when to use it (after completing a task), making the purpose distinct and actionable.
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 instructs to call this tool after completing a task or response. It also explains possible return values and how to handle them, including when to stop calling (USER_DECLINED) or when to continue.
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. Dates show when Glama detected each change.
v1.0.0chat_hookWith only one tool, there is no possibility of confusion. The tool's purpose is clearly distinct.
The single tool name 'chat_hook' uses a consistent underscore convention, which is fine for a single tool.
The server has only one tool, which is at the low end of acceptable. While it serves a specific purpose, typically servers have more tools to cover broader functionality.
The single tool fully covers the server's purpose of user interaction. It handles input and special cases (decline, cancel) through return values, so no gaps are apparent.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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