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Antigravity MCP Orchestrator

Antigravity MCP Orchestrator

Model Context Protocol (MCP) server connecting Google Gemini and local workflows to Google Antigravity IDE.
Works on Linux, macOS, and Windows with zero external Python dependencies.

PyPI version MCP Protocol Python Platforms License

Quick Start • Overview • Gemini Setup • Tools (18) • Brand Kit (ZIP)


Overview

Google Gemini cloud services connect to external MCP servers over public HTTPS URLs. This server exposes an HTTP/SSE interface for Gemini while providing direct access to the local Antigravity IDE workspace, including:

  • Discovery and inspection of 160+ skills across workspace, global, and plugin scopes.
  • Inspection of plugins (cursor-team-kit, pstack, ponytail), rules (GEMINI.md, AGENTS.md), and transcripts.
  • Command execution within the active workspace directory.
  • Dynamic workspace switching at runtime (set_active_workspace) without server restarts.
  • Zero external Python dependencies: implemented with Python's standard library.

Quick Start

Install using pip or execute on-the-fly with uvx / pipx:

# Standard installation
pip install antigravity-mcp

# Or run instantly without pre-installing:
uvx antigravity-mcp --tunnel

2. Install from Source

Clone the repository and execute the setup script:

git clone https://github.com/haydermuhib/gemini-antigravity-orchestrator-mcp.git
cd gemini-antigravity-orchestrator-mcp
chmod +x install.sh && ./install.sh

The script verifies Python 3.10+, checks for cloudflared, installs the antigravity-mcp CLI into ~/.local/bin, and registers the server with local Antigravity IDE configuration.


Prerequisites

  • Python 3.10 or higher
  • Cloudflared (creates the HTTPS tunnel for Gemini Connected Apps)
    • Linux: sudo apt install cloudflared or download from Cloudflare
    • macOS: brew install cloudflared
    • Windows: winget install Cloudflare.cloudflared

Running the Server

Background Service (Linux and macOS)

# Start background server and tunnel
antigravity-mcp start   # or ./start_daemon.sh

# View status and retrieve the active public URL
antigravity-mcp status  # or ./status.sh

# Stop background server
antigravity-mcp stop    # or ./stop_daemon.sh

Foreground Mode

Using Pixi:

pixi run tunnel

Using standard Python:

# Terminal 1: run server on port 8080
python3 server.py --http 8080

# Terminal 2: open tunnel
cloudflared tunnel --url http://127.0.0.1:8080

On Windows (Command Prompt or PowerShell):

python server.py --tunnel

Connecting to Google Gemini Connected Apps

  1. Start the server using one of the methods above.
  2. Run ./status.sh or copy the HTTPS tunnel URL:
    https://<subdomain>.trycloudflare.com/sse
    
  3. In Google Gemini, navigate to Settings > Connected Apps > Connect to an MCP server.
  4. Configure the connection fields:
    • MCP server URL: https://<subdomain>.trycloudflare.com/sse
    • Client ID: gemini-client (or any string)
    • Client secret: gemini-secret (or any string)
  5. Click Connect. Gemini validates the endpoint and loads the tool catalog.

Local Antigravity IDE Configuration (Stdio)

To configure the server inside Google Antigravity IDE, Claude Desktop, or Cursor, add it to your mcp_config.json:

Option A: Direct PyPI Execution via uvx (No clone required)

{
  "mcpServers": {
    "antigravity-orchestrator": {
      "command": "uvx",
      "args": [
        "antigravity-mcp",
        "--stdio"
      ]
    }
  }
}

Option B: Local Source / Development

{
  "mcpServers": {
    "antigravity-orchestrator": {
      "command": "python3",
      "args": [
        "/path/to/gemini-antigravity-orchestrator-mcp/server.py",
        "--stdio"
      ],
      "env": {
        "PYTHONUNBUFFERED": "1"
      },
      "disabled": false
    }
  }
}

Available Tools

The server provides 18 tools to connected models:

Tool Name Description Key Arguments
get_antigravity_status Returns IDE status, workspace path, tool/rule counts, and runtime info. None
list_known_workspaces Lists detected workspaces on the machine and shows which is active. None
set_active_workspace Switches the active workspace to another project directory at runtime. workspace_path (required)
list_skills Discovers skills across workspace, global, builtin, and plugin scopes. scope, plugin_filter
get_skill Retrieves SKILL.md text and metadata for a given skill. skill_name (required)
search_skills Searches skills using keyword matching. query (required)
list_plugins Lists installed plugins, manifests, versions, and subagents. None
get_plugin_details Returns full details of a plugin and its configuration. plugin_name (required)
list_rules Discovers active rules in workspace and global settings. None
get_rule Reads the content and trigger conditions of a rule. rule_identifier (required)
list_conversations Lists recent conversation IDs and brain artifacts. None
get_conversation_transcript Reads recent steps, user inputs, and tool calls from transcript.jsonl. conversation_id, limit
list_artifacts Lists markdown reports and diffs in the conversation brain. conversation_id
read_artifact Reads the markdown content of an artifact file. artifact_name_or_path (required)
execute_workspace_command Executes shell commands in the workspace with exit code, stdout, and stderr. command (required), cwd, timeout
create_workspace_skill Scaffolds a new Antigravity skill directory and SKILL.md. name, description, instructions, scope
create_workspace_rule Creates or updates an Antigravity rule in .agents/rules/. filename, content, scope, trigger
orchestrate_agent_workflow Generates an execution plan matching task intent with skills and rules. task (required), preferred_aesthetic

Protocol Transports

  1. Server-Sent Events (SSE): GET /sse and POST /message?sessionId=<id>
  2. Streamable HTTP POST: POST / and POST /mcp
  3. Stdio Protocol: python3 server.py --stdio

Testing

Run the automated test suites:

# HTTP, SSE, OAuth, HEAD pre-flight, and static asset tests
python3 test_http_mcp.py

# Stdio JSON-RPC 2.0 protocol and 18-tool verification
python3 test_mcp.py

License

MIT License. See LICENSE for details.

Metadata

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