Build LinkedIn GTM workflows in Codex without rebuilding the workflow layer
Zevari gives Codex-style agents a controlled LinkedIn and GTM MCP surface for research, drafting, campaign preparation, and approval requests.
How Codex works with Zevari
- Compose workflow scripts
Use Codex to draft TypeScript or shell workflows that call Zevari MCP tools with explicit review points.
- Connect internal context
Pair LinkedIn-related tasks with internal notes, ICP logic, target lists, or other MCP-accessible systems.
- Prepare outreach assets
Generate connection-note options, DM drafts, reply suggestions, and campaign steps before approval.
Common workflows
- Research prospects before outreach
Ask your AI client to research people, companies, triggers, and context before writing the first message.
- Draft LinkedIn connection notes, DMs, and content
Generate channel-aware outreach and content that matches your positioning, ICP, tone, and the prospect context.
- Stage actions for review
Prepare connection requests, replies, comments, follow-ups, content, and campaign actions in Zevari before sensitive actions execute.
- Classify replies and inbox intent
Turn inbound conversations into next steps, hot leads, follow-up tasks, and pipeline updates.
Safety controls
- Confirmation gates
Sensitive write actions, including messages, comments, connection requests, content publishing, and campaign activation, are routed through review boundaries.
- Account-level controls
Zevari applies pacing, duplicate prevention, stale-state checks, and account-state checks before risky GTM actions proceed.
- Reviewable workspace state
Operators can inspect staged work, recent activity, blocked actions, pending approvals, signals, campaigns, and inbox context in Zevari.