magic-context

★ 2.4k

iot-dc3

★ 1.3k

magic-context vs iot-dc3

Q: Which is better, magic-context or iot-dc3?

By GitHub stars, magic-context has more community adoption, but the best choice depends on your specific use case.

magic-context: Magic Context is a context and memory plugin for coding agent harnesses (OpenCode, Pi and OMP) that compresses history in the background, lifts decisions and conventions into project memory and recalls them each turn. It replaces the host's built-in compaction so one session per project can run for weeks without pauses.; iot-dc3: IoT DC3 is an open-source industrial IoT runtime that connects field devices through 36 protocol drivers (Modbus, OPC UA, Siemens S7, MQTT, LoRaWAN and more) and delivers normalized point data to applications through one API. An Agentic Center built on Spring AI and an MCP tool gateway let AI agents query and act on devices with governance.

TL;DR

magic-contextMemory & Context · ★ 2.4k

Keep one coding-agent session per project running for weeks

Read magic-context full review →

iot-dc3Data Processing · ★ 1.3k

Collecting telemetry from PLCs and sensors on a factory floor into one platform

Read iot-dc3 full review →

Side-by-Side Comparison

Field

magic-context

iot-dc3

Features

magic-context

01Background history compression that lifts durable knowledge into project memory

02Overnight dreamer agents verify, deduplicate and curate memories

03Automatic recall each turn plus search across memories, past conversations and git history

04Setup wizard that configures OpenCode, Pi or OMP and disables built-in compaction

iot-dc3

0136 driver modules covering industrial protocols (Modbus, OPC UA/DA, S7, BACnet, IEC 61850, DNP3) and IoT protocols (MQTT, CoAP, LwM2M, BLE, Zigbee, LoRaWAN)

02MCP tool gateway with OAuth client registration for external AI agents

03Driver SDK for building and registering custom protocol drivers

04PostgreSQL persistence with TimescaleDB, pgvector and AGE

05One-command startup with Podman / Docker Compose, plus Swarm scaling

Use Cases

magic-context

↳Keep one coding-agent session per project running for weeks

↳Avoid compaction pauses that drop context mid-task

↳Give an agent memory of past decisions and project conventions

iot-dc3

↳Collecting telemetry from PLCs and sensors on a factory floor into one platform

↳Letting AI agents query device status and run governed control actions over MCP

↳Decoupling device integration from application development in industrial projects

Best For

magic-context

EssentialTrending

iot-dc3

Trending

FAQ

What is the difference between magic-context and iot-dc3?

Both magic-context and iot-dc3 are in the Memory & Context category. magic-context has 2.4k stars, while iot-dc3 has 1.3k stars.

Which is better, magic-context or iot-dc3?

The best choice depends on your use case. Choose magic-context if Keep one coding-agent session per project running for weeks, and iot-dc3 if Collecting telemetry from PLCs and sensors on a factory floor into one platform.

Is magic-context free or open source?

Yes, magic-context is open source on GitHub (MIT).

Is iot-dc3 free or open source?

Yes, iot-dc3 is open source on GitHub (NOASSERTION).

Cloud Infrastructure

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Alternatives to magic-context →Alternatives to iot-dc3 →magic-context details →iot-dc3 details →

TL;DR

Side-by-Side Comparison

Features

Use Cases

Best For

FAQ

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