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Add Salient to Gemini

Connect Salient's MCP server to Google Gemini CLI or Gemini Enterprise.

Gemini CLI (stdio)

Gemini CLI supports stdio MCP servers natively. Add Salient to your settings file:

Edit ~/.gemini/settings.json:

Edit %USERPROFILE%\.gemini\settings.json:

{
  "mcpServers": {
    "salient": {
      "command": "python3",
      "args": ["/path/to/salient/tools/mcp-ttx/server.py"],
      "env": {
        "SALIENT_API_URL": "http://localhost:8000",
        "SALIENT_TOKEN": "your-jwt-token"
      }
    }
  }
}

Restart Gemini CLI after saving. Verify with:

gemini
# Then ask: "List my Salient scenarios"

No token needed for local dev

When running Salient locally with make dev, leave SALIENT_TOKEN empty.

Gemini Enterprise (Google Cloud)

For Gemini in Google Cloud (Vertex AI), you need to register a custom MCP connector:

  1. Open Google Cloud Console > Vertex AI > Gemini
  2. Navigate to Extensions or Custom Connectors
  3. Create a new MCP connector with your remote Salient MCP endpoint URL
  4. Set authentication to Bearer token with your SALIENT_TOKEN

Remote server required

Gemini Enterprise requires an HTTP MCP endpoint. See the Remote MCP Server guide.

Consumer Gemini Web App

The consumer Gemini web app (gemini.google.com) does not currently support custom MCP servers. Use Gemini CLI for local setups or Gemini Enterprise for cloud deployments.

What Works

Once connected, Gemini can access all 40+ Salient tools:

  • Browse and run tabletop exercises
  • Query the digital twin
  • Generate posture assessments and playbooks
  • Sync identity connectors (Okta, Entra ID)

Tools Reference · MCP Overview