AgiFlow AI Plugin

Official AgiFlow plugin for AI coding clients. Drive AgiFlow project management — planning, grooming, execution, and review — directly from your AI coding tool.

Works with Claude Code, Codex, Cursor, Antigravity, and Gemini CLI.

How to develop

git clone <your-remote>/agiflow-ai-plugin
claude --plugin-dir ./agiflow-ai-plugin

• Add new workflow instructions under skills/<name>/SKILL.md.
• Keep shared guidance in references/ (e.g. references/agiflow-agents.md).
• See references/plugin-types.md for per-client manifest notes.

Features

This plugin connects to the AgiFlow MCP server (https://agiflow.io/api/v1/mcp) and exposes AgiFlow tools across these categories:

• Projects — create, inspect, and update projects and their statuses
• Tasks — create, list, get, update, reorder, and batch-create tasks
• Work units — group tasks into deliverable features/epics and track progress
• Workflows — acquire/release locks and coordinate multi-agent runs
• Members — list and assign agent members to work
• Comments — document decisions and progress on tasks
• Vault — read and set scoped configuration entries

Bundled skills

The plugin ships 10 workflow skills that mirror AgiFlow's scrum pipeline. Your AI client loads them on demand when your request matches their description — you generally don't invoke them by name:

Shared guidelines (status model, transitions, tags, work-unit sizing) live in references/agiflow-agents.md.

Self-hosted

For a self-hosted AgiFlow instance, point the MCP wiring at your endpoint via the AGIFLOW_AI_PLUGIN_MCP_URL environment variable (consumed by gemini-extension.json):

export AGIFLOW_AI_PLUGIN_MCP_URL="https://mcp.your-agiflow-instance.com/api/v1/mcp"

For other clients, edit the server URL in .mcp.json, mcp.json, and mcp_config.json.

Documentation

• AgiFlow: https://agiflow.io
• Plugin client compatibility: references/plugin-types.md

Installation

This repo is a self-contained, multi-client plugin bundle. Until it is published to each client's marketplace, load it as a local plugin directory.

Claude Code

git clone <your-remote>/agiflow-ai-plugin
claude --plugin-dir ./agiflow-ai-plugin

The bundled .mcp.json wires the AgiFlow MCP server automatically. Use /mcp inside Claude Code to check the connection.

Antigravity (Google)

Place the plugin folder in one of Antigravity's plugin locations, then restart:

# Workspace-level (this project only)
mkdir -p .agents/plugins && cp -R /path/to/agiflow-ai-plugin .agents/plugins/

# Global (all workspaces)
mkdir -p ~/.gemini/config/plugins && cp -R /path/to/agiflow-ai-plugin ~/.gemini/config/plugins/

Antigravity reads the root plugin.json marker, the skills/, and mcp_config.json automatically.

Cursor

Add manually in Cursor Settings → MCP / Plugins, pointing at this folder. Cursor's stable surface is MCP config — the bundled .mcp.json provides it.

Codex

Add the AgiFlow plugin marketplace, then install the plugin from that marketplace:

codex plugin marketplace add AgiFlow/ai-plugin
codex plugin add agiflow-ai-plugin@agiflow

For local development, point Codex at this checkout as a marketplace root:

codex plugin marketplace add ./agiflow-ai-plugin
codex plugin add agiflow-ai-plugin@agiflow

Gemini CLI

gemini extensions install <your-remote>/agiflow-ai-plugin

The bundled gemini-extension.json connects the AgiFlow MCP server via mcp-remote.

Example usage

> Plan a feature: add per-user notification preferences
> Groom the backlog and promote the ready tasks to Todo

> Run task DXX-2
> Execute the checkout work unit end-to-end

> Review the auth work unit against its acceptance criteria
> Give me a daily standup for this project

> Why is this project stuck?
> What should an agent pick up next?

License

MIT