Skip to main content
AI coding agents work best when they understand your systems, APIs, and tools. The superglue CLI ships with a skill — a structured reference that teaches agents how to use every sg command, handle auth, build tools, and debug failures. Install once, works across 35+ agents.

​
Installing the CLI

npm install -g @superglue/cli

​
Setup

Interactive setup: 
sg init
Prompts for your API key (get one at app.superglue.cloud/admin), endpoint, and output preferences. Environment variables (CI, AI agents, non-interactive): 
export SUPERGLUE_API_KEY="your-api-key"
export SUPERGLUE_API_ENDPOINT="https://api.superglue.cloud"  # optional, this is the default
Verify: sg system list — if you see fetch failed or auth errors, double-check your API key and endpoint.

​
Installing the Skill

The skill gives your AI agent full CLI knowledge — commands, auth patterns, tool schemas, debugging, and deployment. Install once and the agent references it automatically.

​
Universal Install (all agents)

npx skills add superglue-ai/cli
Auto-detects your installed agents. Target a specific agent with -g -a <agent>: 
npx skills add superglue-ai/cli -g -a claude-code
npx skills add superglue-ai/cli -g -a codex
npx skills add superglue-ai/cli -g -a cursor

​
Agent-Specific Install

From the Anthropic marketplace:
/plugin install superglue@claude-plugins-official
Or load from local install:
claude --plugin-dir $(npm root -g)/@superglue/cli

​
What the Skill Provides

  • All CLI commands with flags, options, and usage patterns
  • Authentication patterns — credential placeholders, OAuth flows, header formats
  • Tool configuration schema — step configs, data selectors, transforms, pagination
  • Debugging workflows — common errors, --include-step-results, sg system call for isolation
  • Deployment patterns — SDK, REST API, webhooks (via references/integration.md)
  • Specialized references for databases, file servers, and transforms (loaded on demand)

​
Adding Project-Specific Context

The skill teaches the AI how to use superglue. Add a section to your project’s AI config file (CLAUDE.md, AGENTS.md, or .cursorrules) so it knows to use the skill and discover your setup dynamically: 
## Using Superglue

When working with superglue tools — via the CLI, SDK, or REST API:

1. Invoke the superglue skill and read the SKILL.md file before running any sg command
2. Read the relevant reference files for the task (integration, databases, file-servers, transforms)
3. Ensure the CLI is configured (sg init has been run or env vars are set)
4. Run sg system list and sg tool list to discover the current setup before building or modifying anything
5. Never hardcode system IDs or tool IDs — always discover them dynamically

​
Best Practices

​
Always test systems before building tools

Have the agent run sg system call to verify auth and see the actual response shape before constructing a tool config: 
sg system call --system-id stripe \
  --url "https://api.stripe.com/v1/customers?limit=2" \
  --headers '{"Authorization":"Bearer <<stripe_api_key>>"}'

​
Use --include-step-results when debugging

Shows the raw API response from each step — pinpoints whether the issue is auth, the endpoint, or a transform: 
sg tool run --draft <id> --payload '{}' --include-step-results

​
Never paste secrets into chat

Use --sensitive-credentials when creating systems via the CLI so secrets are prompted securely: 
sg system create --id my_api --url https://api.example.com \
  --credentials '{"client_id":"abc"}' \
  --sensitive-credentials client_secret,api_key

​
LLM-Readable Documentation

For agents that don’t support skills, we provide full docs in LLM-friendly formats:
FileURLPurpose
Indexllms.txtLightweight index of all pages
Full docsllms-full.txtComplete documentation in one file
If your tool can fetch URLs — give it the URL. If it requires file uploads — download llms-full.txt and upload directly.

​
Support & Resources