Skip to main content

Dekart CLI for auth, MCP tool discovery, calls, and file upload flows.

Project description

dekart-cli

Dekart MCP wrapper for your AI agent to create maps from SQL query results.

Works best with the geosql skill — it writes the SQL, this CLI renders the map.

Works with any Dekart instance:

  • Dekart Cloud (SaaS, default)
  • Self-hosted (your own URL)
  • Localhost (http://localhost:8080)

Init

pip install dekart
dekart init

dekart init walks you through:

  1. Picking the instance (Cloud / self-hosted / localhost).
  2. Authorizing the CLI in your browser.
  3. Optionally enabling local snapshots.

To switch instance later:

dekart config --url <your-url>
dekart init

Config and token: ~/.config/dekart/.

Enable local snapshot

Local headless renderer for fast PNG snapshots without a round-trip to the server:

dekart snapshot-local install

Manage:

dekart snapshot-local status
dekart snapshot-local uninstall          # remove renderer
dekart snapshot-local uninstall --purge  # also remove its browser cache

When local snapshot is enabled, dekart snapshot --report-id <id> --out ./snap.png uses it automatically. Pass --remote-only to force server-side rendering.

Run Prepared Query And Download Rows

Run an already-prepared Dekart query, wait for the job, and save result rows:

dekart run-query --query-id <query-id> --out-dir ./results --wait --json

Queries wait by default; use --no-wait only when you expect an already-finished job. Prepare the query separately with dekart call --name create_query and dekart call --name update_query, then use dekart run-query to run, poll, and download the result. Use --json to return dataset_id, query_id, job_id, terminal status, and result_file metadata. Empty downloads fail with empty result (metadata/SHOW statement?).

Resolve a report URL explicitly from a report id:

dekart report-url --report-id <report-id>
dekart report-url --report-id <report-id> --json

Preview Downloaded Rows

Preview a CSV or parquet file produced by dekart run-query:

dekart preview ./results/<result-file>.parquet --limit 20
dekart preview ./results/<result-file>.parquet --schema

Preview output is tab-separated. Parquet and CSV previewing use the bundled DuckDB Python dependency.

Links

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dekart-0.11.0.tar.gz (33.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dekart-0.11.0-py3-none-any.whl (25.4 kB view details)

Uploaded Python 3

File details

Details for the file dekart-0.11.0.tar.gz.

File metadata

  • Download URL: dekart-0.11.0.tar.gz
  • Upload date:
  • Size: 33.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for dekart-0.11.0.tar.gz
Algorithm Hash digest
SHA256 6b23551c39c0489f98b12ee4ead175265880149fec76ef9ac7fca96773508849
MD5 a4cccbc23791fea6636a4b70a3bc7075
BLAKE2b-256 1c728d0a419ea125a3927709a7fea071817879a1111f3582e75fb1c41e841e55

See more details on using hashes here.

File details

Details for the file dekart-0.11.0-py3-none-any.whl.

File metadata

  • Download URL: dekart-0.11.0-py3-none-any.whl
  • Upload date:
  • Size: 25.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for dekart-0.11.0-py3-none-any.whl
Algorithm Hash digest
SHA256 16415aefe1ca87ff57834f9b8816b39cd0a1a4ed2f0fc7f23a19899da8d4ba8c
MD5 ca37ae1fc84499d407144281d32c0a55
BLAKE2b-256 c112d2c7c84980cef064a89f6f5449924367f1053f11df3e99bd66a7285fed7b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page