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FieldWorks

Composable, open, MCP-native. Protocol-first, multi-agent, designed to run fully on-premises in air-gapped environments.

FieldWorks

An open source industrial AI framework. Protocol-first, plant-agnostic, runs on-premises.

FieldWorks gives industrial facilities a natural language interface to their own process data. Connect it to your existing protocol infrastructure, describe your plant, and operators can diagnose faults and query plant status in plain English. No cloud dependency. Air-gap ready.

Repositories

Repo Language Description
fieldworks-core Python Topology validation, specialist prompt generation, aggregator configuration
fieldworks-adapters Rust Conformant MCP protocol adapters — MQTT, OPC-UA, Modbus, DNP3, EtherNet/IP, AVEVA
fieldworks-examples Python, Rust Dependency-free examples for the Fieldworks industrial AI framework
fieldworks-spec Framework specification v0.1

Reference implementation

waterworks-ai — a complete industrial AI deployment built on FieldWorks. Water treatment plant scenario, multi-agent diagnostics, reactive monitoring, four-store memory architecture.

Status

Active development. v0.1 in progress.

License

Apache 2.0

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  1. fieldworks-adapters fieldworks-adapters Public

    Conformant MCP protocol adapters for industrial systems. Rust workspace — mqtt-mcp, opcua-mcp, modbus-mcp, dnp3-mcp, ethernetip-mcp, aveva-mcp.

    Rust

  2. fieldworks-core fieldworks-core Public

    Python core for the FieldWorks industrial AI framework. Topology validation, specialist prompt generation, and aggregator configuration.

    Python

  3. fieldworks-examples fieldworks-examples Public

    Minimal, dependency-free examples for the Fieldworks industrial AI framework — one script per primitive: topology, specialist prompts, tool scoping, trust, and memory.

    Python

Repositories

Showing 6 of 6 repositories

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