Polymetrics CLI

One CLI to rule them all.

pm is a local-first data CLI for ETL, embedded DuckDB SQL, reverse ETL, scheduling, and AI-agent-safe automation. It runs as one Go binary, keeps credentials local, and speaks JSON everywhere.

Website · Docs · Quickstart · Agent Contract · Contributing

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Polymetrics turns the whole operational data loop into a command-line workflow:

source -> extract -> local warehouse -> DuckDB SQL -> plan -> preview -> approve -> write back

No hosted control plane is required for the first useful run. Use it on a laptop, in CI, in cron, in a container, or inside an LLM agent pod with the same command surface.

What It Does

Surface	What you get
ETL	Pull records from APIs, databases, local files, and catalog-backed connectors.
SQL	Query extracted data locally with an embedded DuckDB engine.
Reverse ETL	Write results back through approval-gated destination actions.
Agents	Use --json, stable exit codes, and no silent mutation paths.
Catalog	Track a 646-connector catalog with active native Go ports.
Runtime	Keep credentials in an encrypted local vault. No server required.

Quickstart

Build from source:

git clone https://github.com/polymetrics-ai/cli
cd cli
make build
./pm version

Run a local extract and query loop with the sample connector:

export PM_SAMPLE_TOKEN=demo

./pm init
./pm credentials add sample --connector sample --from-env token=PM_SAMPLE_TOKEN
./pm credentials add warehouse --connector warehouse --config path=.polymetrics/warehouse
./pm connections create demo \
  --source sample:sample \
  --destination warehouse:warehouse \
  --stream customers \
  --primary-key id \
  --cursor updated_at \
  --table customers

./pm etl run --connection demo --stream customers --json
./pm query run --table customers --limit 5 --json

Release binaries are published on GitHub:

gh release download --repo polymetrics-ai/cli --pattern 'pm_*_darwin_arm64.tar.gz'

Why It Exists

Data work is usually split across a pipeline service, a warehouse, a reverse ETL product, a scheduler, and a separate automation interface. Polymetrics puts the developer loop first: install one binary, connect a source, inspect data, run SQL, then write back only after an explicit approval step.

This makes the tool useful for:

• Developers who want local-first ETL without provisioning infrastructure.
• Data engineers who need reproducible extract, query, and reverse ETL flows.
• AI agents that need a stable CLI contract instead of brittle prose parsing.
• Open-source contributors who want connector work to be small and testable.

Agent Contract

Polymetrics is designed for humans and LLM agents to drive the same commands.

pm etl run --connection github --stream issues --json
pm query run --sql "select * from issues where state = 'open'" --json
pm reverse plan sync --source-table stale_issues --destination github:write --json

The contract is intentionally boring:

• --json returns versioned envelopes on stdout.
• Progress and logs go to stderr.
• Exit codes separate usage, validation, auth, connector, runtime, policy, and internal failures.
• Reverse ETL is split into plan, preview, approve, and run.
• Secrets are referenced by field name and never printed.

Connectors

Use the CLI to inspect what is available in your binary and what is planned in the catalog:

pm connectors list
pm connectors list --all
pm connectors inspect github --json
pm connectors port-plan --all --json

The repository tracks a 646-connector catalog. Enabled connector support is expanding through native Go ports built on shared SDK primitives for auth, pagination, retries, schema inference, read streams, and write actions.

Architecture

flowchart LR
  CLI["pm CLI / agent"] --> SRC["Sources"]
  SRC --> WH[("Local warehouse")]
  WH --> SQL["DuckDB SQL"]
  SQL --> PLAN["Plan and preview"]
  PLAN --> DEST["Destinations"]

Loading

• internal/connectors contains per-system connector packages.
• internal/app owns ETL, query, reverse ETL, scheduling, and automation flows.
• cmd/pm exposes the CLI.
• docs contains generated manuals and connector documentation.
• website publishes the docs, connector catalog, blog, llms.txt, and sitemap.

Search And AI Discovery

The canonical description is:

Polymetrics CLI is a local-first data CLI for single-binary ETL, embedded DuckDB SQL, reverse ETL, connector automation, and AI agent data workflows.

The README, docs, website metadata, blog, sitemap, and llms.txt use the same terms deliberately so humans, search engines, and AI answer engines can identify the project without keyword stuffing.

Canonical topics:

• local-first data CLI
• single-binary ETL
• embedded DuckDB SQL engine
• reverse ETL CLI
• AI agent data workflows
• connector catalog
• approval-gated writes

Contributing

Connector PRs are the best first contribution. Start with the setup guide, copy an existing connector package, add focused tests, and run verification before opening a PR.

make verify
make verify-duckdb

Use Conventional Commits:

• fix(github): handle paginated issue labels
• feat(connector): add source-linear
• docs(readme): clarify local-first quickstart

Roadmap

• Local CLI runtime
• JSON output and stable exit-code contract
• Local encrypted credential vault
• ETL, query, and approval-gated reverse ETL
• Release binaries
• Website docs, connector catalog, blog, sitemap, and llms.txt
• More native connector ports from the 646-connector catalog
• Homebrew tap
• Bundled MCP server
• Hosted examples and reproducible benchmark datasets

License

Elastic License 2.0 (c) 2026 Polymetrics AI.

Polymetrics CLI is public source and free to use under Elastic License 2.0. The license does not permit offering the software to third parties as a hosted or managed service where users access a substantial set of its functionality. For commercial licensing beyond those terms, contact Polymetrics AI.