EGC vs Maced AI

EGC and Maced AI are both coding assistants tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

EGC

EGC is a local-first MCP runtime that persists memory across sessions and across AI tools, so agents pick up exactly where the last session stopped. The repo structure shows explicit support for Cursor, Codex, Gemini, Kiro, Trae, and OpenCode, meaning the memory layer sits beneath whichever assistant you switch to. The system tracks completed tasks, failures, and next steps automatically — you do not write the handoff notes. The wall appears when you need a hosted or API-accessible version: the vendor describes no hosted runtime, no remote API, and no paid tier, so teams requiring cloud-accessible memory or multi-user session state have nowhere to go within this tool.

Maced AI

Maced deploys AI agents that crawl, fuzz, and attempt exploitation across your web apps, APIs, source code, and cloud infrastructure — then deliver audit-grade reports with proof-of-exploit payloads and merge-ready fix PRs. Every finding is auto-validated before it surfaces, which means triage queues shrink instead of growing. The continuous monitoring model means your attack surface is tested on every deploy, not just once a quarter. The ceiling shows up when your environment demands the kind of adversarial creativity a seasoned human tester brings to a novel business-logic flaw — agents that follow a structured probe loop will miss what only lateral thinking finds. Teams with that requirement use Maced for baseline and point a human at what the agents flag as high-severity.

Attribute	EGC	Maced AI
Pricing	Free	Paid
Price	—	$249/mo
Free trial	No	No
Open source	Yes	No
Has API	No	Yes
Self-hosted option	Yes	Yes
Platforms	Local / desktop	Web-based SaaS; on-premises and air-gapped deployment available
Pros	Zero-prompt memory restoration on session start, which means developers stop spending the first part of every session re-explaining project state to an agent that forgot everything. Single memory layer spanning multiple AI coding assistants — Cursor, Codex, Gemini, Kiro, Trae, and OpenCode are all covered — so switching tools mid-project does not fragment your context into incompatible silos. Automatic tracking of completed tasks, failures, and next steps, which means the handoff document you never wrote still exists when you return after two weeks away. MIT license with a local-first runtime and self-hosted option, so your project memory never touches an external server and the tool cannot be deprecated behind a paywall. Install scripts and pre-built agent configuration files ship with the repo, which means the integration surface for supported tools is a config file change rather than a custom integration build.	Auto-validation with proof-of-exploit payloads for every finding, so your team stops spending sprint time manually reproducing scanner noise before deciding whether to act. Merge-ready fix PRs generated and retested automatically, which means remediation moves from 'ticket in backlog' to 'reviewed and merged' without a separate engineering investigation cycle. Continuous scanning triggered on every deploy rather than quarterly, so a misconfiguration introduced in Tuesday's PR is caught before it reaches production — not six weeks later in an audit. SOC 2 and ISO 27001 audit-ready report output, so compliance documentation is a byproduct of your normal security workflow rather than a separate manual engagement you schedule and budget for. Self-hosted deployment option, so teams operating in air-gapped or strict data-residency environments can run the platform without routing source code or infrastructure details through a third-party cloud.
Cons	No hosted runtime and no API surface: any workflow that requires memory to be accessible from a remote server, a CI pipeline, or a second developer's machine has no path forward inside EGC. Teams needing shared or cloud-accessible session state have to build their own persistence layer or switch to a tool that offers one. With 17 open GitHub issues and no paid support tier, production bugs in edge cases — unsupported assistant versions, memory corruption on interrupted sessions, schema mismatches after updates — land entirely on the team to diagnose and fix. Teams that cannot absorb that maintenance overhead typically move to a commercially supported memory layer. Coverage is limited to the AI coding assistants explicitly wired into the repo. If your tool of choice lacks a configuration directory in the project, memory persistence does not apply to it, and adding support requires contributing to the project or maintaining a fork.	Agents follow a structured crawl-fuzz-exploit loop, which means multi-step business-logic attacks that require contextual judgment — an attacker who knows your domain and chains three unrelated weak points — fall outside what the platform reliably discovers. Teams whose threat model centers on that class of vulnerability still require a human penetration tester; Maced becomes a first-pass filter, not a full engagement replacement. The platform is paid-only with no free tier beyond an initial scan, so teams evaluating at scale against a large or complex environment cannot fully assess fit before committing to a subscription — at which point switching cost is real if the agents' coverage does not match the environment's actual attack surface. White-box testing requires handing over source code access, and for teams at organizations where that creates legal, contractual, or procurement friction, onboarding stalls at the approval stage rather than the technical one — a problem self-hosting solves only if your ops team has bandwidth to stand up and maintain the infrastructure.

Bottom line

EGC is free while Maced AI is paid; EGC is open source; only Maced AI exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between EGC and Maced AI?

EGC is Free and open source, while Maced AI is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is EGC better than Maced AI?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.

EGC vs Maced AI: which should I pick?

Pick EGC if its pricing model, openness, or platform fit matches your constraints; pick Maced AI otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.