Skip to main content
Glama

When using AI CLIs/IDEs, agents can drift from your intent. This project gives you a simple way to intervene at key moments, review context in a Web UI, and send your latest instructions via interactive_feedback so the agent can continue on track.

Works with Cursor, VS Code, Claude Code, Augment, Windsurf, Trae, and more.

Quick start

  1. Install:

pip install ai-intervention-agent

# or
uv add ai-intervention-agent
  1. Configure your AI tool to launch the MCP server via uvx:

{
  "mcpServers": {
    "ai-intervention-agent": {
      "command": "uvx",
      "args": ["ai-intervention-agent"],
      "timeout": 600,
      "autoApprove": ["interactive_feedback"]
    }
  }
}
NOTE

>interactive_feedback is a long-running tool. Some clients have a hard request timeout, so the Web UI provides a countdown + auto re-submit option to keep sessions alive.

- Only ask me through the MCP `ai-intervention-agent` tool; do not ask directly in chat or ask for end-of-task confirmation in chat.
- If a tool call fails, keep asking again through `ai-intervention-agent` instead of making assumptions, until the tool call succeeds.

ai-intervention-agent usage details:

- If requirements are unclear, use `ai-intervention-agent` to ask for clarification with predefined options.
- If there are multiple approaches, use `ai-intervention-agent` to ask instead of deciding unilaterally.
- If a plan/strategy needs to change, use `ai-intervention-agent` to ask instead of deciding unilaterally.
- Before finishing a request, always ask for feedback via `ai-intervention-agent`.
- Do not end the conversation/request unless the user explicitly allows it via `ai-intervention-agent`.

Screenshots

Key features

  • Real-time intervention: the agent pauses and waits for your input via interactive_feedback

  • Web UI: Markdown, code highlighting, and math rendering

  • Multi-task: tab switching with independent countdown timers

  • Auto re-submit: keep sessions alive by auto-submitting at timeout

  • Notifications: web / sound / system / Bark

  • SSH-friendly: great with port forwarding

VS Code extension (optional)

Item

Value

Purpose

Embed the interaction panel into VS Code’s sidebar to avoid switching to a browser.

Install (Open VSX)

Open VSX

Download VSIX (GitHub Release)

GitHub Releases

Setting

ai-intervention-agent.serverUrl (should match your Web UI URL, e.g. http://localhost:8080; you can change web_ui.port in config.jsonc.default)

Configuration

Item

Value

Docs (English)

docs/configuration.md

Docs (简体中文)

docs/configuration.zh-CN.md

Default template

config.jsonc.default (on first run it will be copied to config.jsonc)

OS

User config directory

Linux

~/.config/ai-intervention-agent/

macOS

~/Library/Application Support/ai-intervention-agent/

Windows

%APPDATA%/ai-intervention-agent/

Architecture

flowchart TD
  subgraph CLIENTS["AI clients"]
    AI_CLIENT["AI CLI / IDE<br/>(Cursor, VS Code, Claude Code, ...)"]
  end

  subgraph MCP_PROC["MCP server process"]
    MCP_SRV["ai-intervention-agent<br/>(server.py)"]
    MCP_TOOL["MCP tool<br/>interactive_feedback"]
    CFG_MGR["Config manager<br/>(config_manager.py)"]
    NOTIF_MGR["Notification manager<br/>(notification_manager.py)"]
  end

  subgraph WEB_PROC["Web UI process"]
    WEB_SRV["Web UI service<br/>(web_ui.py / Flask)"]
    HTTP_API["HTTP API<br/>(/api/*)"]
    TASK_Q["Task queue<br/>(task_queue.py)"]
    WEB_SRV --> HTTP_API
    WEB_SRV --> TASK_Q
  end

  subgraph USER_UI["User interfaces"]
    BROWSER["Browser"]
    VSCODE["VS Code extension<br/>(Webview)"]
  end

  CFG_FILE["config.jsonc<br/>(user config directory)"]

  AI_CLIENT -->|MCP call| MCP_TOOL
  MCP_SRV -->|exposes| MCP_TOOL

  MCP_TOOL -->|ensure Web UI running| WEB_SRV
  MCP_TOOL <-->|create task / poll result| HTTP_API

  BROWSER <-->|HTTP| HTTP_API
  VSCODE <-->|HTTP| HTTP_API

  CFG_MGR <-->|read/write| CFG_FILE
  WEB_SRV <-->|read| CFG_FILE

  MCP_SRV --> NOTIF_MGR
  NOTIF_MGR -->|web / sound / system / Bark| USER["User"]

Documentation

License

MIT License

Install Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

Resources

Looking for Admin?

Admins can modify the Dockerfile, update the server description, and track usage metrics. If you are the server author, to access the admin panel.

Latest Blog Posts

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/XIADENGMA/ai-intervention-agent'

If you have feedback or need assistance with the MCP directory API, please join our Discord server