Agents that reason, act, and collaborate.
The AI Agent node is a true reasoning runtime. Multi-agent teams share memory, debate, and ship — model-agnostic, tool-equipped, and MCP-ready.
What it does.
Reasoning runtime
Agents plan, call tools, and adapt — not single-shot prompts.
Multi-agent teams
Specialized roles share memory and hand off work.
MCP-ready
Connect any MCP server to give agents new tools in minutes.
Model-agnostic
Pick the best model per task; swap without re-platforming.
Tool use
Web, CMS, CRM, warehouse — agents act on real systems.
Memory
Grounded in your knowledge base, brand voice, and past work.
A reasoning runtime, not a prompt box.
Give the agent a goal and it plans the steps, calls tools, observes the results, and adapts until it's done — bounded by the tool-call limit and instructions you set.
Tools, datasources, and MCP — wired in.
Equip an agent with exactly the abilities a task needs. It calls them on its own as it reasons.
Pick the right brain for each agent.
Choose a reasoning-capable model per node — GPT-4, Claude Sonnet/Opus, or Gemini Pro — and tune temperature, top-K, top-P, and max tokens. Swap models without re-platforming.
From input to outcome.
Define the goal
Drop an AI Agent node into Studio, write the system prompt, and set the tool-call limit — no code required.
Attach capabilities
Equip the agent with tools, MCP servers, and RAG datasources so it can act on real systems.
Run and observe
Fire the workflow — watch the agent plan, call tools, and adapt step by step in the execution log.
Review and refine
Inspect every reasoning step and tool call, tune the prompt or tools, and iterate until it ships reliably.
Show us the workflow.
We'll show you the 10x.
Bring the marketing workflow that eats your week. We'll build it live, with your data and your models, in 30 minutes.