Integrate Agent700 Agent with

1000+ apps and services

Agent700 is an AI agent platform that lets you run trusted agents with alignment data and context. This community package adds two custom n8n nodes so you can call those agents and manage their context directly from your workflows—with App Password auth, no manual token handling, and support for batch processing, error handling, and encrypted key/value storage.
What you get
Agent700 Agent – Send messages to any Agent700 agent from a workflow. You specify the agent (by ID), the message (with full n8n expression support), and optional simplified output. The node uses your App Password to authenticate and wraps the message in the API format. Use it for one-off Q&A, content analysis, URL or document evaluation, and as a building block in multi-step or batch workflows.
Agent700 Context Library – Manage key/value “alignment” data that agents can use as context. Data is stored with encryption at rest. The node supports full CRUD: create, update, upsert, delete, get one entry, and list all entries. It also supports pattern-based query (e.g. glob-style keys) and Query + Construct to build JSON from matching entries via a template—so you can feed dynamic, structured context into your Agent node or other nodes.
Authentication and security
All nodes use Agent700 App Password API credentials (no copy-paste of short-lived tokens).
You set a Base URL (default https://api.agent700.ai) and your App Password (e.g. app_a7_ + 32 characters) in the credential; the nodes obtain and use access tokens for you.
App passwords can be scoped and revoked in the Agent700 UI, and you can use n8n’s credential storage and different passwords per environment (e.g. dev/staging/prod).
Typical use cases
Chat and Q&A – Manual or trigger-based workflows that send a question to an agent and use the reply (e.g. in a notification or another node).
Content and URL evaluation – Fetch URLs or content, loop over them, send each to the Agent node for analysis (e.g. privacy or compliance), then store or aggregate results with the Context Library.
Context-driven conversations – Use the Context Library to store user preferences, session data, or domain context; then send that context (or template-built JSON) in the message to the Agent node for personalized or context-aware answers.
Batch and pipelines – Combine with “Split In Batches,” error handling, and “Continue on Fail” for robust bulk processing and fallbacks.
Technical details
Nodes: Agent700 Agent, Agent700 Context Library.
Credentials: Agent700 App Password API (Base URL + App Password).
Compatibility: Built for current n8n Node API; Node.js 18+.
Install: npm install @a700/n8n-nodes-agent700 then restart n8n; nodes appear under Agent700 Agent and Agent700 Context Library.
Usable as tool: Both nodes are marked usableAsTool: true for agentic/sub-workflow use where supported.
Docs and support
README and workflow examples (simple chat, context injection, URL evaluation, batch processing, error handling) are in the repo.
For API and product details: https://agent700.readme.io/
Package: @a700/n8n-nodes-agent700 on npm.