Agency Agents vs Zamp

Agency Agents and Zamp 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.

Zamp

The vendor describes a four-day onboarding arc — connect your existing tools, walk through your process, correct the agent's early runs, then hand off volume. Testimonials from Mindbody's finance team confirm invoice processing runs end-to-end with human review only when Zamp surfaces a question. It monitors and executes without waiting for a prompt, which separates it from chatbot-style tools. The ceiling appears where process logic is genuinely novel or where your team's judgment call changes week to week — Zamp learns from correction, but that feedback loop takes cycles to stabilize. Pricing is opaque until you book a demo, and there is no self-hosted deployment path.

Attribute	Agency Agents	Zamp
Pricing	Free	Paid
Free trial	No	No
Open source	Yes	No
Has API	No	No
Self-hosted option	Yes	No
Platforms	macOS, Linux, Windows	Web/SaaS (app.zamp.ai)
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.	Connects to existing tools — ERPs, inboxes, spreadsheets — without an IT integration project, so your team does not lose months before the agent is running on real work. Runs processes end-to-end without a prompt each cycle, so your team is not the bottleneck managing a tool that should be managing itself. Learns from each correction and applies that learning across all future similar tasks, which means the error rate compounds downward instead of requiring someone to manually update a rule tree every time a new exception appears. Escalates to humans when it hits a genuine decision point rather than silently failing or dropping work, so the output your team sees has already been filtered for the cases the agent cannot resolve. Covers a wide range of operational roles — finance, compliance, HR, customer success — so a single deployment can absorb repetitive work across departments rather than requiring a separate tool per function.
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.	Processes that change frequently — seasonal policy updates, evolving compliance rules, shifting approval hierarchies — require ongoing correction cycles that never fully stabilize; teams in those environments report a sustained supervisory burden rather than true hands-off automation. There is no self-hosted or on-premise deployment option. For financial institutions or healthcare operations with hard data residency requirements, this is not a configuration gap — it is a disqualifier. Teams in those environments move to vendors with private cloud or on-prem options rather than working around it. The feedback-learning model means the agent's accuracy in the first weeks depends entirely on the quality and volume of corrections your team provides; teams that under-invest in the day-three review phase report slower accuracy gains and extend the period where human oversight is heavy rather than light.

Bottom line

Agency Agents is free while Zamp is paid; Agency Agents is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Agency Agents and Zamp?

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

Is Agency Agents better than Zamp?

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.