n8n + Claude Code Agent Coordinator
A Telegram-triggered n8n workflow that routes messages to a LangChain agent (via OpenRouter) with buffered memory, custom tools, and an SSH node that runs commands against a remote Claude Code session — built to coordinate multiple agent tasks from a chat interface.
What this template does
A Telegram-triggered n8n workflow that routes messages to a LangChain agent (via OpenRouter) with buffered memory, custom tools, and an SSH node that runs commands against a remote Claude Code session — built to coordinate multiple agent tasks from a chat interface. It's categorized in our directory under Dev & Agent Automation — agent coordination, CI/CD glue, and developer-tool integrations — including our own Claude Code + n8n templates.
Integrations
- n8n
- Telegram
- OpenRouter
- Claude Code
Setup steps
- 1Wire a Telegram bot as the trigger and connect it to the workflow's Telegram Trigger node.
- 2Configure the LangChain Agent node with an OpenRouter chat model and a buffered-window memory node so context persists across messages.
- 3Add the SSH node's connection details for the remote host running Claude Code.
- 4Register the custom Code and Workflow tool nodes the agent can call to delegate sub-tasks.
- 5Test end to end from Telegram: send a task, confirm the agent routes it through SSH and returns a result.
More Dev templates
Other dev & agent automation templates in our directory.
n8n Claude Code Terminal Bridge
A minimal n8n workflow that exposes a chat trigger, formats the incoming message with a Set node, and pipes it over SSH into a running Claude Code CLI session — the smallest possible bridge between a chat UI and a real terminal agent.
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How we standardize repeatable engineering work as versioned Claude Code skills, so every build starts from a proven playbook — publishing, audits, image pipelines, SEO checks, and deploy safety are all captured as skills, not one-off prompts.
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Our end-to-end process for shipping an AI-native product feature: scoping the real user workflow first, prototyping against production-shaped data, and shipping behind a flag with evals in place before it's exposed to real users.