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MCP Integration

Salient is built for the age of AI agents. It exposes a full MCP (Model Context Protocol) server with 40+ tools that let any compatible AI agent manage exercises, query the digital twin, sync connectors, and compile security intelligence.

Salient is also an MCP client — it can consume data from external MCP servers (Gmail, Notion, Google Calendar, Slack, etc.) and feed it into your digital twin.

Quick Setup

One command:

claude mcp add salient-ttx -- python3 tools/mcp-ttx/server.py

Or add to your project .mcp.json:

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

Full Claude Code Setup

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

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

Full Claude Desktop Setup

Salient's MCP server uses stdio transport and follows the standard MCP protocol. Any client that supports stdio MCP servers can connect:

  • Command: python3 tools/mcp-ttx/server.py
  • Environment: SALIENT_API_URL, SALIENT_TOKEN
  • Protocol: JSON-RPC 2.0 over stdin/stdout

All Platforms

Platform Transport Guide
Claude Code stdio Setup
Claude Desktop stdio Setup
ChatGPT / OpenAI HTTP Setup
Google Gemini stdio / HTTP Setup
Amazon Bedrock HTTP Setup
Cursor stdio Setup
VS Code / Copilot stdio Setup
Windsurf stdio / HTTP Setup
JetBrains IDEs stdio Setup
Cline stdio Setup
Remote / Hosted HTTP Setup

What You Get

Once connected, your AI agent has access to:

Category Tools What They Do
Exercises list_scenarios, get_scenario, create_scenario, save_session, save_evaluation Browse, run, and score tabletop exercises
Twin Intelligence query_twin, twin_facts, twin_facts_summary, detect_patterns, recommend_scenario Query the digital twin, detect recurring gaps, get scenario recommendations
Posture posture_assessment, posture_report, posture_timeline Generate board-ready security posture assessments
Connectors okta_sync, entra_id_sync, list_connectors, twin_coverage, discover_connector Sync identity data, analyze coverage gaps
Threat Intel ingest_threat_intel, list_threat_intel, generate_scenario_from_intel Ingest threat articles, generate targeted scenarios
MCP Ingestion ingest_from_mcp, ingest_document, list_mcp_sources Feed data from sibling MCPs into the twin
Playbooks generate_playbook, get_playbook Generate incident response playbooks from exercise results
Dashboard get_dashboard, get_org_profile Get platform stats and org profile

The /ttx Skill

If you're using Claude Code, the /ttx skill provides guided workflows:

/ttx              Run a tabletop exercise
/ttx profile      Review digital twin completeness
/ttx gather       Guided evidence collection
/ttx evaluate     Re-evaluate a past exercise
/ttx playbook     Generate an incident response playbook
/ttx enrich       Pull data from available sibling MCPs
/ttx status       Dashboard overview

Two-Way MCP

Salient doesn't just serve data to AI agents — it consumes data from them.

Path 1: AI-Mediated — When Claude has access to Gmail, Calendar, Notion alongside Salient, the /ttx enrich command orchestrates across all of them. Security-relevant emails, policy documents, calendar events flow into your twin automatically.

Path 2: Direct Client — Salient's backend connects to external MCP servers directly, discovers their tools and resources, and syncs data into the twin.

Sibling MCP Orchestration · MCP Client