AI Platform
Use your favorite coding agent to build, deploy and manage applications on Nodion. Over MCP, the CLI or the REST API.
Works with the coding agents you already use
Anthropic's agentic coding tool, right in your terminal.
OpenAI's coding agent, in the terminal or the IDE.
The AI code editor, with one-click MCP setup.
The open-source coding agent for any model.
Connect
Pick what your agent speaks. All three use the same API and the same project permissions.
Nodion runs a hosted MCP server at https://mcp.nodion.net. Cursor and Claude Code use a personal API key from Account → Security. ChatGPT, Codex, and Claude Desktop use OAuth. No local daemon.
nodion login for the CLI. For MCP, create a key at Account → Security.# terminal claude mcp add nodion --transport http https://mcp.nodion.net \ --header "Authorization: Bearer nodion_…"
Other clients: one-click setup for Cursor and Claude Code, or the MCP docs. Write actions ask you to confirm before they run.
The nodion CLI talks to the same API as the dashboard. Agents that can run shell commands should follow auth.md, then install, sign in and deploy.
# install curl -fsSL https://cli.nodion.net/install.sh | bash # sign in (device code flow), or set NODION_API_TOKEN in CI nodion login # deploy the current repo nodion projects use prj_… nodion link nodion deploy --wait
Full reference in the CLI docs.
Any agent that can make HTTP requests can drive Nodion. Every endpoint lives under https://api.nodion.com/v2/ and takes a bearer token.
# list applications curl https://api.nodion.com/v2/applications \ -H "Authorization: Bearer $NODION_TOKEN" \ -H "X-Nodion-Project: $NODION_PROJECT" # trigger a deployment curl -X POST https://api.nodion.com/v2/applications/$APP_ID/deployments \ -H "Authorization: Bearer $NODION_TOKEN" \ -H "Content-Type: application/json" -d '{}'
Every endpoint, payload and response in the API reference.
Capabilities
Full access to the platform from your coding session, with you in the loop for every write.
Trigger deployments, follow the build and check that the release is healthy.
Read application logs, spot the error and suggest a fix without leaving the session.
Check CPU and RAM per process and catch performance problems early.
Write a Dockerfile for your project, or let buildpacks detect the stack.
Set environment variables and secrets, and attach databases and buckets.
Change instance counts and sizes per process when traffic changes.
Example
The agent reads the project, picks a build, deploys and checks the result.
# ask the agent to deploy > deploy this repo to nodion detected Rails 7.1, PostgreSQL 16, Node 20 wrote Dockerfile created app my-api in project prod # push, the build streams live > git commit -am "deploy" && git push deployment #42: building, release, health check live at https://my-api.euc.nodion.app # ask what is running > what is running on my-api? my-api available dockerfile, 2 instances last deployment #42 by you: "deploy"
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