How to choose an AI-agent platform: the six things that actually matter

Picking an agent platform is less about finding "the best" and more about matching a tool to your constraints. To keep comparisons honest, we score every platform on the same six dimensions. Here is what each one means and how to weigh it for your own decision.

The six dimensions

• Developer experience (dx) — how quickly a competent developer gets from zero to a working agent: SDK quality, docs, and the mental model you have to adopt.
• Pricing — not "how cheap," but how predictable and transparent. A platform with clear, forecastable costs scores higher than one with many metered dimensions.
• Scalability — how well the platform runs real, concurrent, long-lived workloads.
• Memory — built-in persistence and long-term memory versus "bring your own store."
• Integrations — the breadth and quality of connectors, tools, and channels.
• MCP-nativeness — how deeply the platform supports the Model Context Protocol.

Every platform's scorecard is on its dossier under /platforms, and the full rubric is on our methodology page.

How the dimensions trade off

No platform maxes out all six, and the shape of the trade-off tells you what a platform is for:

• SDKs like the Vercel AI SDK and OpenAI Agents SDK score top marks on pricing (free, MIT — you pay only token costs) and strong dx, but leave memory and orchestration to you.
• Infrastructure like Modal and Fly.io Machines leads on scalability and dx, but is compute — not an agent framework, so integrations and built-in memory are lower.
• Frameworks like LangGraph balance memory, integrations, and scalability, at the cost of a steeper mental model and metered managed pricing.
• Managed platforms trade some transparency and control for turnkey channels and hosting.

A practical way to weigh them

Rather than chase the highest average, weight the dimensions that map to your actual risk:

• Building a product on top? Prioritise dx and pricing predictability.
• Running agents 24/7? Prioritise scalability and memory — see how to run an agent 24/7.
• Automating across many SaaS tools? Prioritise integrations and MCP-nativeness.
• Cost-sensitive or experimenting? Start with free-to-start options.

The comparison tool at /compare lines any two platforms up on all six dimensions, so you can see the trade-off instead of arguing about a single number.

Key takeaways

• Score platforms on six dimensions: dx, pricing, scalability, memory, integrations, MCP-nativeness.
• "Pricing" means predictability, not just cost.
• No platform wins on all six — the shape of the trade-off reveals what a platform is built for.
• Weight the dimensions to your use case, then compare side-by-side at /compare.