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Connect an Agent

Connect

Connecting an agent makes your rules available to it. See how gnt works for how that pairs with check_action to actually stop an unapproved action.

claude.ai connectors

In claude.ai, go to Settings → Connectors → Add custom connector. Paste your MCP endpoint (from gnt keys create) as the server URL, then add an Authorization: Bearer gnt_live_xxxx header with your key. All 5 tools become available in any chat once it's connected.

Claude Code

Create a named key in the dashboard and copy its one-command setup, or print the same artifact from the CLI:

Code
gnt keys create "Claude Code — production" --client claude-code

That command connects the MCP server. Claude Code is also the one supported client where gnt can install a host hook that mechanically checks tool calls before they run:

Code
gnt hooks install

Codex

Choose Codex when creating an agent key. gnt prints the supported ~/.codex/config.toml remote server entry with its authorization header. The Codex app, CLI, and IDE extension share that MCP configuration. Codex does not currently expose a CLI flag that durably stores this static authorization header, so gnt labels this honestly as Copy config, not as a one-command connection.

Code
gnt keys create "Codex — production" --client codex

This makes check_action and the other gnt tools available. gnt does not install a Codex host interceptor today, so your runtime or tool adapter must call check_action before side effects.

Gemini CLI

Gemini CLI supports a remote streamable HTTP MCP server with an authorization header. The dashboard and CLI both generate its supported one-command setup:

Code
gnt keys create "Gemini CLI — recruiting" --client gemini

This connects the tools only. gnt does not install a Gemini host interceptor today; enforce check_action in the runtime or tool adapter.

Generic MCP client

Choose Generic MCP for a portable server URL and authorization-header template:

Code
gnt keys create "Support runtime" --client generic

MCP access alone does not intercept the client's other tools. The host must place gnt at its action boundary.

Raw MCP client (Python)

Talk to the endpoint directly over streamable HTTP with the official MCP SDK.

Code
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client

URL = "https://api.gntai.dev/mcp/"
TOKEN = "gnt_live_xxxx"

async with streamablehttp_client(
    URL, headers={"Authorization": f"Bearer {TOKEN}"}
) as (read, write, _):
    async with ClientSession(read, write) as session:
        await session.initialize()
        result = await session.call_tool(
            "search_rules", {"query": "refund window"}
        )

OpenAI-compatible agent

The Responses API supports remote MCP servers as a tool type. Point it at the same endpoint and header.

Code
from openai import OpenAI

client = OpenAI()
resp = client.responses.create(
    model="gpt-4.1",
    input="What is our refund policy?",
    tools=[{
        "type": "mcp",
        "server_label": "gnt-brain",
        "server_url": "https://api.gntai.dev/mcp/",
        "headers": {"Authorization": "Bearer gnt_live_xxxx"},
    }],
)

OpenClaw

Run gnt connect openclaw to detect a local install and write this for you, or add it to ~/.openclaw/openclaw.json by hand and export GNT_MCP_KEY before starting the gateway. Connecting only makes the tools available, so pair it with the check_action skill below: that's what gets OpenClaw to actually call it before acting, not just have it on hand.

Code
{
  "mcp": {
    "servers": {
      "gnt-brain": {
        "url": "https://api.gntai.dev/mcp/",
        "transport": "streamable-http",
        "headers": { "Authorization": "Bearer ${GNT_MCP_KEY}" }
      }
    }
  }
}

Hermes Agent

Nous Research's Hermes Agent reads MCP servers straight out of its own config file. Run gnt connect hermes to wire it up, or see the Hermes Agent page for the full walkthrough, including the skill that gets Hermes to call check_action before it acts.