Agency Agents vs Krater

Agency Agents and Krater are both ai agent apps 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.

Agency Agents

The project is a MIT-licensed, self-hostable collection of pre-defined agent definitions organized by domain — engineering, marketing, product, design, and more — built to be activated inside Claude Code, Cursor, and similar AI coding tools. Each agent carries a defined personality, a stated process, and expected deliverables, so the session opens with role context already loaded. The differentiator is breadth plus specificity: you are not configuring a blank agent; you are picking a specialist with an opinionated approach baked in. The ceiling appears when your workflow requires branching between agents at runtime or dynamic handoffs — the repo defines agents, it does not orchestrate them. Teams needing cross-agent coordination wire that logic themselves on top.

Krater

The core workflow is a unified chat interface where you route requests to different models — GPT-4, Claude, Gemini, image generators, audio tools — without context-switching between platforms. Slash commands and scheduled tasks let you automate recurring generation jobs inside the same workspace. The ceiling appears when your workflow needs branching: Krater executes single-turn commands well, but it does not plan multi-step tasks or loop through tool use on its own. Teams building anything that requires a model to react to its own previous output and decide a next action will hit that wall quickly. At that point, they move to a purpose-built orchestration layer and use Krater's API access for model calls.

Attribute	Agency Agents	Krater
Pricing	Free	Paid
Price	—	$9/mo
Free trial	No	No
Open source	Yes	No
Has API	No	Yes
Self-hosted option	Yes	No
Platforms	macOS, Linux, Windows	Android (with Chrome), iOS (with Safari), Windows (with Chrome or Edge), macOS (with Chrome)
Released	—	2023
Pros	Pre-defined personality and process per agent, so sessions open with role context already loaded rather than you spending the first exchanges re-establishing what the model should be doing. MIT license with self-hosted install options (install.sh and brew command documented in the repo), so the definitions stay on your infrastructure and are not gated behind a vendor's API or auth layer. Organized by domain directory — engineering, marketing, product, design, finance, and others — so a team can adopt only the agents relevant to their work without importing unrelated definitions. Community fork count and open contribution model mean the agent library grows through pull requests, so domain gaps can be filled without waiting for a vendor roadmap. Personality-driven definitions that go beyond bare system prompts, which means the model's tone and decision-making style stays consistent across sessions rather than varying with however the user frames the first message.	Access to 350+ models under one subscription with no per-provider API key management, so teams stop juggling separate billing accounts when they need to compare output from GPT-4, Claude, and Gemini on the same task. Multi-format generation — text, images, video, audio, code — in one workspace, which means you produce a full marketing asset set without logging into four separate platforms mid-campaign. Scheduled tasks and automation inside the workspace, so recurring content jobs run without manual triggering each cycle. API access included, so developers prototyping across model providers can route calls through a single integration point instead of maintaining separate SDK configurations for each provider. Freemium entry tier lets small teams evaluate real model output before committing budget, avoiding the situation where you discover a tool's output quality only after purchasing an annual plan.
Cons	No built-in runtime coordination between agents: when a task requires one agent to trigger or hand off to another based on output, you write that logic yourself — and at more than two or three agents, you are maintaining a separate orchestration layer that is not part of this repo. No API surface is provided, so any team that wants to call these agent definitions programmatically from their own application has to extract and adapt the definition files manually rather than consuming them via an endpoint. The definitions are only as current as the last accepted pull request — if a domain evolves (a new framework standard, a changed marketing platform) and the community has not merged an update, the agent's stated process drifts from reality, and you get confidently outdated guidance. Teams that need agents to run tasks autonomously across a multi-step pipeline — rather than as session-scoped personas — will exhaust what this repo offers and migrate to a full agent framework (LangGraph, Dify, or similar) that treats coordination and state as first-class concerns, at which point these definitions become input prompts to a larger system rather than the system itself.	Krater executes single-turn commands — it does not autonomously plan, branch, or chain steps based on previous model output. Any workflow that requires a model to inspect its own result and decide a next action without user input is out of scope; teams handling that use case add a separate agent framework and use Krater only for model call routing. No self-hosted option exists, which means teams with data residency requirements or enterprise security policies that prohibit third-party SaaS handling model inputs cannot deploy Krater in their stack — those teams move to open-source multi-model interfaces they can run on their own infrastructure. The free guest tier caps daily usage at three messages, which is insufficient for evaluating the tool on any realistic content workflow; meaningful quality assessment requires a paid tier, so the freemium entry point functions more as a feature preview than a genuine trial.

Bottom line

Agency Agents is free while Krater is paid; Agency Agents is open source; only Krater exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Agency Agents and Krater?

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

Is Agency Agents better than Krater?

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.