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Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
extensions
{
  "io.modelcontextprotocol/ui": {}
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
interactive_feedbackA

Ask the human user for interactive feedback through the Web UI.

Use this tool whenever you need a human decision, clarification, confirmation, plan approval, design review, or final sign-off before continuing — especially when the next step has multiple valid approaches, irreversible side effects, or significant trade-offs.

Behavior:

  • Renders the resolved message (Markdown) and an optional list of options in a Web UI; the user submits text + selected options + optional images.

  • The call blocks until the user submits, the auto-resubmit countdown expires, or the configured backend timeout is reached.

  • On success, returns a list of MCP content blocks (text + image) that include the user reply, selected options, and an optional prompt suffix.

  • On parameter validation failure, raises ToolError so the agent can retry with corrected arguments. On service / task failure, returns a configurable resubmit prompt instructing the agent to call this tool again, instead of silently dropping the request.

Cross-tool compatibility:

  • summary / prompt are accepted as aliases for message so the same mcp.json config can target other feedback MCP variants without retraining the agent.

  • options is an alias for predefined_options.

  • project_directory, submit_button_text, timeout, timeout_seconds, feedback_type, priority, language, tags, user_id, task_id are accepted but ignored. They prevent the first-call validation failures observed when an agent reuses arguments shaped for a different feedback MCP server.

Note: this function is not the MCP registration site itself; server.py wraps it with mcp.tool() to expose it to MCP clients.

R25.2: 函数体首行 import httpx 让下面 except httpx.HTTPError 在运行时 解析符号——本工具被 MCP 客户端首次调用时一次性付 ~55 ms 加载费,而 MCP server cold-start 路径完全不会进入此函数(server.py 顶层 import 时只是定义而已)。

R44 FastMCP 最佳实践:ctx 关键字参数(FastMCP 自动注入)让本函数可以走 await _emit_ctx_info(ctx, ...) 把 task lifecycle 事件回送给 client (Cursor / Claude Desktop / ChatGPT Desktop)。client 收到后会在 chat sidebar 渲染一行进度日志,让人类用户能"看到工具确实在工作、正在等真人 回复",而不是猜"agent 是不是 hung 住了"。ctx 永远 keyword-only 且 默认 None,所以本工具被通过别的入口(pytest 直接调)调用时不会因为缺 ctx 而崩;具体安全语义见 _emit_ctx_info 的 docstring。

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
Server InfoSelf-information for ai-intervention-agent MCP server. Returns version, transport, runtime details, middleware chain, accumulated error stats, Web UI runtime status, and task-queue snapshot as JSON.

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