Ecosystem

ActQL Ecosystem

github.com/actql

Cross-system SQL and workflows, integrated with the tools you already use.

ActQL is the SQL-based data & workflow engine for AI agents. Read across SaaS and databases, join and transform data, and take action — with an LLM where a judgment is needed — with typed checks, pushdown optimization, and reliable execution.

Use ActQL directly through SQL, AQL, or its official SDKs, or from the tools you already use: database drivers, dbt, and Python DataFrames, with agents connecting through MCP. Bring cross-system data processing and actions into your stack without changing it.

ActQL Cloud provides managed execution and operations.

One engine. Many ways to build.

                 EXISTING DEVELOPER ECOSYSTEMS

   SQL / dbt / BI     TS / Python / Apps      Agents / MCP
          │                    │                     │
          └────────────────────┼─────────────────────┘
                               ▼
  ┌──────────────────────────────────────────────────────────┐
  │                          ActQL                           │
  │             SQL-based data & workflow engine             │
  │    SQL / AQL → Typed Plan → Pushdown → Run / Effects     │
  └──────────────────────────────────────────────────────────┘
                               │
                               ▼
                          Connectors
                       SaaS / DB / Graph
                        Vector / Stream

                  Local · Edge · ActQL Cloud
                 Execution and hosting options

Core

1.ActQL Engine & Connectors

SQL-based execution, capability-aware planning, local and remote runtimes.

ActQL Enginein development
The SQL-based data & workflow engine for AI agents.
actql/actql
ActQL Connectorsin development
Capability-aware integrations with databases, SaaS APIs, files, and compute engines
actql/actql

Agents

2.Agent Tools & MCP

Turn ActQL programs into typed tools that agents can call through MCP.

MCPcoming soon
ActQL tools for MCP-compatible agents and applications

Existing ecosystems

3.SQL, Data & Application Integrations

ActQL Drivers · dbt · Python / Polars / pandas

ActQL Driverscoming soon
ADBC, JDBC and ODBC connectivity for existing SQL tools
actql/actql-drivers
dbt-actqlcoming soon
dbt adapter for ActQL
actql/dbt-actql
Python and DataFramescoming soon
Python SDK, DataFrame integration with Polars, pandas and Ibis, and typed Pydantic models

Managed

4.ActQL Cloud

Managed execution, connections, agent tools and stack operations.

ActQL Cloudcoming soon
Managed execution, connections, agent tools and stack operations