ai-intervention-agent
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
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
Install:
pip install ai-intervention-agent
# or
uv add ai-intervention-agentConfigure 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"]
}
}
}>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`.Related MCP server: AI Intervention Agent
Screenshots
Key features
Real-time intervention: the agent pauses and waits for your input via
interactive_feedbackWeb 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) | |
Download VSIX (GitHub Release) | |
Setting |
|
Configuration
Item | Value |
Docs (English) | |
Docs (简体中文) | |
Default template |
|
OS | User config directory |
Linux |
|
macOS |
|
Windows |
|
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
API docs index:
docs/api/index.mdAPI docs (简体中文):
docs/api.zh-CN/index.md
Related projects
License
MIT License
This server cannot be deployed
Maintenance
Related MCP Connectors
Human-in-the-loop for AI agents over MCP: durable approvals with a hosted review page & audit trail
Agent-ready feedback for AI-built apps — read and close UI feedback reports over MCP.
Human-in-the-loop control panel for AI agents: start runs, review them, answer their requests.
Impri MCP server — human-in-the-loop approval inbox for AI agents
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to request human input through a web interface, allowing them to pause execution and wait for responses via interactive tools like single questions, multiple choice selections, hypothesis challenges, and decision workflows.12 npm2MIT
- AlicenseAqualityAmaintenanceEnables real-time user intervention for MCP agents through a web UI, allowing users to review context and provide feedback when AI agents drift from intent, keeping them on track.21199 PyPI16MIT
- AlicenseNot gradedqualityBmaintenanceEnables human-in-the-loop checkpoints for AI agents, allowing them to pause and wait for human input via a web UI, then seamlessly resume execution.37MIT
- FlicenseNot gradedqualityDmaintenanceEnables agents to request and receive user feedback during task execution through a terminal-based interactive feedback system.10-