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15. Nansen CLI

Nansen CLI brings Nansen data into the terminal for developers, power users, and AI agents. It is especially useful when you want a fast, scriptable workflow without depending on the browser UI.

Installation​

npm install -g nansen-cli

If you are using an AI-agent environment, you can also load the related skill files:

npx skills add nansen-ai/nansen-cli

Authentication​

Use one of the following methods:

nansen login --api-key <key>
nansen login --human
export NANSEN_API_KEY=...
nansen logout

The environment variable has the highest priority and is often the best choice for scripts and servers.

Command groups​

  • nansen research <category> <subcommand>
  • nansen trade <subcommand>
  • nansen wallet <subcommand>
  • nansen schema [command] [--pretty]

Research categories include smart-money, token, profiler, portfolio, prediction-market, search, perp, and points.

Important options​

  • --chain <chain> to choose the network
  • --limit <n> to constrain output
  • --timeframe <tf> for time windows such as 24h or 7d
  • --fields <list> to keep responses compact
  • --sort <field:dir> to order the output
  • --table for quick visual output
  • --pretty for readable JSON
  • --stream for large datasets

Practical examples​

Smart Money net flow on Solana​

nansen research smart-money netflow --chain solana --timeframe 24h --limit 10 --table

Analyze a known wallet by ENS​

nansen research portfolio show --address vitalik.eth --pretty

Reduce output size for agent workflows​

nansen research smart-money netflow --chain solana --fields token_symbol,net_flow_usd --limit 10

How to read responses​

A successful response uses a standard wrapper:

{"success": true, "data": {}}

Errors look like this:

{"success": false, "error": "message", "code": "UNAUTHORIZED", "status": 401}

Important error codes to remember:

  • CREDITS_EXHAUSTED
  • UNAUTHORIZED
  • RATE_LIMITED
  • UNSUPPORTED_FILTER

Best practices​

  • Use nansen schema --pretty before exploring a new command
  • Limit payload size with --fields when using LLM or agent workflows
  • Use --stream for large outputs
  • Prefer environment variables in production environments

Reference​