AI Intervention Agent

You can manage and guide MCP agents in real time with an Intervention Agent server. It lets you pause an AI workflow, review context in a Web UI, and send your latest instructions back to the agent to keep it aligned with your intent. It works with popular AI clients and IDEs to keep sessions alive and on track.

How to use

Start the Intervention Agent as an MCP server and connect it from your AI client. You’ll send ongoing instructions through the interactive feedback loop, review the agent’s context in a Web UI, and let the agent continue with new guidance.

Key usage patterns you’ll perform routinely:

How to use

• Launch the MCP server via your client configuration so that the AI tool can invoke the agent’s interactive feedback stream.

• When the agent needs guidance or clarification, use the interactive feedback channel to supply instructions, ask clarifying questions, or switch strategies.

• Review results and context in the Web UI, then send updated instructions to keep the task on track.

• If the session is about to time out, rely on the Web UI automatic re-submit to keep the session alive and continue the task.

How to install

Prerequisites: make sure you have Python 3.7+ and a compatible package manager installed.

Install the Intervention Agent package using Python’s package manager.

pip install ai-intervention-agent

How to install

Alternate installation method using the UV tool if you prefer to manage MCP servers via UV.

uv add ai-intervention-agent

Configuration and running

Configure your AI client to launch the MCP server using the UV command gateway so that the agent can receive interactive feedback.

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

What to expect in the Web UI

The Web UI displays the current task context, allows you to send interactive_feedback, and shows a countdown so you can re-submit before timeout.

Notes and tips

interactive_feedback is a long-running tool. Web UI sessions include a countdown and auto re-submit option to keep sessions alive.

If a tool call or action fails, continue sending feedback through the ai-intervention-agent channel instead of guessing or making final decisions in chat.

Architecture overview

The Intervention Agent pairs with AI clients to provide a real-time feedback loop, a Web UI for context review, and a mechanism to propagate your latest instructions back to the agent as it executes tasks.

Available tools

interactive_feedback

MCP tool that allows real-time feedback to steer the agent, review context, and guide subsequent actions within the session.