Agentic setup

OpenTide exposes the engine to AI agents through an MCP server and portable agent skills, so an assistant in your editor can search the catalogue, validate objects, and preview deploys. This page sets it up, shows a realistic session, and is honest about what agents can and cannot do today.

What agents can and cannot do today

Install and configure the server

pip install 'opentide==0.1.0'
opentide setup mcp --cursor --yes

This writes .cursor/mcp.json:

{
  "mcpServers": {
    "opentide": {
      "command": "opentide-mcp",
      "env": { "OPENTIDE_REPO_ROOT": "${workspaceFolder}" }
    }
  }
}

The server uses stdio transport. It must know where your content lives, so set OPENTIDE_REPO_ROOT in the host environment (as above). If the server fails to start, see MCP configuration.

Supported hosts

Install agent skills

Skills give the agent durable, project-specific instructions (object layout, commands, the validate-before-deploy rule):

Browse the catalogue, then install selected skills from OpenTideHQ/skills:

opentide setup skills discover
opentide setup skills discover --query sentinel
opentide setup skills show opentide-detection-rule

opentide setup skills --yes --generic \
  --name "SOC Detections" \
  --org "Example Corp" \
  --description "Enterprise MDR content"

opentide setup skills --yes --install opentide-detection-rule --install detection-engineering

After setup, point your agent at the generated AGENTS.md at the repo root — it is the entry point for detection work in your repository.

A safe agent workflow

Give agents this loop. It searches, validates, and only ever previews deploys.

flowchart LR
  search["search()<br/>find relevant objects"] --> read["read object + get_chaining()"]
  read --> edit["propose YAML edit"]
  edit --> validate["validation_report()"]
  validate -->|pass| dryrun["deploy_rule(dry_run=true)"]
  validate -->|fail| edit

Example session

You: Add a rule for T1059 credential access on Sentinel.

Agent: search(query="T1059") → finds the Credential Access objective …8002…0001. get_chaining(uuid="…8002…0001") → confirms it covers the Simulated Actor threat and has no rule yet. Proposes objects/rules/sentinel-t1059.yaml with detection_model pointing at the objective. validation_report() → passes schema, uuid, chaining. Runs opentide validate query --platform sentinel (CLI) for real KQL syntax. deploy_rule(uuid=…, platform="sentinel", dry_run=true) → shows the planned change.

You: review the diff, then deploy for real.

Safe vs unsafe edit patterns

Safe — let agents do these

• Search, read, and summarise objects and coverage.
• Draft new objects from templates, filling required fields.
• Run validation_report and surface concrete errors.
• Fix dangling references and vocabulary violations the validator flags.
• Preview deploys with dry_run=true.

Unsafe — keep a human in the loop

• Real (non-dry-run) deploys to production.
• Bulk promotion of rules to PRODUCTION without an explicit human status change and review.
• Editing .opentide/configurations/ credentials or deployment plans.
• Trusting an MCP validate_query "pass" as real syntax validation (it is a stub).
• Regenerating or hand-editing UUIDs to resolve a conflict.

Recommended guardrails in AGENTS.md

Add rules like these to the generated AGENTS.md so the agent respects them:

- Always run `validation_report` before proposing a rule as done.
- Query validation for Sentinel/Defender/Splunk/SentinelOne/Carbon Black MUST use
  the CLI `opentide validate query`; the MCP tool is a stub.
- Never claim query validation for CrowdStrike or HarfangLab — they are deploy-only.
- Deploys are `dry_run=true` unless a human explicitly approves a real deploy.

Reference

• MCP tools and resources — the full agent surface.
• MCP configuration — multi-repo, deploy safety, host specifics.
• Detection-as-code — the human loop agents assist with.