Data Workers Agent Swarm

The Data Workers Agent Swarm is a fleet of specialist agents, each an MCP server, each expert in one slice of data work. They share one context graph, one activation model, and one governed write path — so the fleet behaves like a team, not a pile of tools.

How the swarm is structured

Customer-facing agents do the work you ask for. Platform agents — the connector gateway, orchestration, observability, identity, ingest, review, search, and the Conductor — keep the fleet coherent underneath; you rarely address them directly.

Every agent starts in 🟡 Evaluation on sample data and earns 🟢 Connected per system through a live test — the model is described in Verify your setup.

The customer-facing agents

Agent	What it does
Pipelines & Ingestion	Natural-language-to-pipeline generation, Iceberg MERGE INTO, Airflow deployment, EL/CDC ingestion
Incidents	Statistical anomaly detection, graph-based root-cause analysis, playbook execution
Catalog & Context	Hybrid search (vector + BM25 + graph), lineage traversal, crawlers; home of the context graph
Schema	Schema diffs, rename detection, snapshot-based evolution
Quality	Weighted five-dimension scoring, anomaly detection, 14-day baselines
Data Access & Governance	Policy authoring, entitlement provisioning (grant/revoke/JIT), audit
FinOps & Cost	Usage profiling, warehouse cost estimation, tiered archival
Data & Cloud Security	DSPM + CSPM findings, ranked and routed to the fix
Migration	Oracle/Teradata/Redshift→Snowflake SQL translation with a self-correcting loop
Insights	NL-to-SQL execution, insight generation, anomaly explanation
Usage Intelligence	Practitioner analytics, adoption dashboards, heatmaps — zero-LLM
Streaming	Kafka Connect config generation, lag monitoring, tuning
MLOps & Models	Experiment tracking, model registry, drift detection, A/B testing

Running the swarm

The install paths, from a one-liner to source, are in the onboarding tracks — start at Choose your plan. The short version:

# in any MCP client — the whole fleet
claude mcp add data-workers -- npx -y dw-claw

# or the free five-tool taste
npx data-context-mcp

Self-hosting options — Docker Compose, Kubernetes, air-gapped — are covered in Deployment options.

Design principles worth knowing

• Sample-data-first. Every agent is fully exercisable before any credential exists. What you see in evaluation is the real logic, run on a realistic sample estate.
• Verified, not assumed. No surface shows a system as connected without a passing live test.
• Governed writes. Reads can never mutate. Writes are proposed, approved, executed with a receipt, and auditable — and irreversible actions always require approval.
• Honest capability edges. If a connector or agent doesn’t support an operation, it says so in a structured error instead of pretending. You should never discover a capability gap from silent wrong output.
• Bring your own model. The swarm runs against your model key — frontier, open-weight, or local.