🤖 Agent Loop

Overview

The Agent Loop node runs a multi-turn Claude agent that can call MCP tools and other Falcon nodes you expose to it, looping until the task is done. Use it when a task needs runtime decision-making, multi-step tool use, or iterative refinement — for deterministic single-shot work, prefer the AI Prompt node instead.

When to use Agent Loop vs. AI Prompt

• AI Prompt — one request, one response. Predictable cost, no tool use. Best for classification, transformation, single-shot generation.
• Agent Loop — multi-turn with tools. The model can call MCP servers or sibling Falcon nodes (HTTP, Postgres, send-email, send-SMS, Outlook, Google Sheets, set), receive results, and decide what to do next. Best for triage, research with tools, self-critique-and-revise, agentic workflows.

Configuration

• Anthropic Credential — optional. If set, the workspace pays Anthropic directly (BYOK, zero AI credit consumption). If unset, the platform key is used and tokens are deducted from the workspace AI credit bucket.
• Model — defaults to Claude Sonnet 4.5. Choose Opus for deeper reasoning, Haiku for cheaper/faster runs.
• System Prompt — optional. Supports {{variables}}.
• User Prompt — required. Supports {{variables}}.
• Max Turns — defaults to 10. Hard ceiling: 25.
• Max Tokens — defaults to 1024. Hard ceiling: 8192.
• MCP Servers — multi-select of workspace MCP servers the agent can call.
• Exposed Nodes — multi-select of sibling nodes in the same workflow to expose as agent tools. Supported types: http-request, postgres, send-email, send-sms, set, microsoft-outlook, google-sheets.
• Output Variable — defaults to agent_result. The agent's final response, turn count, stop reason, token usage, and tool-call log are stored here.
• Conversation Memory — same shape as AI Prompt's memory options. Only the final user prompt + final assistant response are persisted between runs (intermediate critique/revision turns are kept in-process).

Operation-multiplexed nodes

For Microsoft Outlook and Google Sheets, the source node MUST have its operation configured before exposing it. Set the operation in the source node's config panel first; the agent then fills only the runtime input, not the operation.

• Outlook operations: message.send, message.reply, message.getMany, message.get, calendarEvent.create, calendarEvent.getMany, calendarEvent.update
• Google Sheets operations: getRange, appendRows, updateRange

Output

The output variable contains:

• response — the agent's final text response
• turns — number of turns consumed
• stopReason — end_turn, max_tokens, etc.
• inputTokens / outputTokens
• toolCalls — array of every tool the agent invoked, with input, result, and error flag

Plan availability

Agent Loop requires PRO or higher on the platform-credit path. FREE tier workspaces can still use Agent Loop by attaching their own Anthropic credential to the node (BYOK) — the workspace pays Anthropic directly with zero AI credit consumption.

Security

• Each tool call runs in an isolated execution context — the agent cannot read or pollute the parent workflow's variable bag.
• Credentials on exposed sibling nodes are fixed at config time. The agent cannot substitute a different credential at runtime.
• MCP servers are scoped to the workspace. Only servers the workspace owns can be referenced.
• Hard ceilings on turns and tokens cap worst-case cost per run regardless of node config.

Required Credentials