pumaDB Review (2026): Pricing, Features & Honest Verdict

What is pumaDB?

pumaDB solves a small but real problem: AI agents forget. Once a session ends, most agents lose everything they learned. pumaDB gives them durable memory by storing structured JSON that survives across sessions, without you having to stand up Postgres, write migrations, or manage a connection pool. The tagline says it plainly: durable memory for agents, without the database work.

It comes in two flavors. There is a hosted MCP server you can plug straight into agent clients like ChatGPT and Claude, and a REST API for server-side applications. So a Claude or ChatGPT agent can write a note now and read it back next week, or your own backend can use pumaDB as a simple record store. We found the framing refreshingly narrow. It is not trying to be a full database. It is trying to be the memory slot an agent needs and nothing more.

The need is real. Anyone who has built with agents knows the frustration of a model that solves a problem brilliantly and then forgets it ever happened. You end up either stuffing everything back into the context window, which gets expensive and unreliable, or wiring up a database, which is a lot of plumbing for what is often just a bag of notes. pumaDB sits in the gap between those two bad options. It is more durable than the context window and far less work than a real database. For a whole class of agent projects, that is exactly the right amount of tool.

What are pumaDB’s key features?

Memory over MCP or REST

The dual interface is the whole point. If you are wiring up an agent in Claude or ChatGPT, you use the hosted MCP server and the agent gets read and write tools for free. If you are building server-side, you hit the REST API. Same storage, two doors. This means you are not locked into one runtime, which is rare in the agent-memory space.

Version history and one-click recovery

Every update and delete is archived. pumaDB keeps 10 versions of a record for 30 days and lets you restore any of them with one click. For agent memory this is more important than it sounds. Agents make mistakes and overwrite good data with bad data. Being able to roll back a single record after an agent went off the rails is a genuine safety net.

Built-in rate limiting and safety

pumaDB caps writes at 30 per minute and reads at 60 per minute per key, which protects you from a runaway agent hammering the store in a loop. It also supports natural language editing of records. The safety rails feel designed by someone who has actually watched an agent misbehave, which is reassuring.

Flexible JSON storage

You store plain JSON, so the same table can hold skills written in markdown, project conventions, user preferences, research notes, or task state. There is no rigid schema to fight. For an agent that needs scratch space across many kinds of data, this flexibility is the right default.

Natural language editing

Records can be edited in plain language rather than by hand-writing JSON patches, which fits the way agents actually operate. An agent can say what it wants changed and pumaDB applies it. This keeps the agent loop simple, since the model does not have to construct precise update payloads to keep its own memory current. It is a small design choice that reflects who the tool is really for: not human database admins, but agents managing their own state.

How much does pumaDB cost?

pumaDB has a free tier with 20 tables, 1,000 rows per table, and 25 MB of total storage per account. That is enough to prototype an agent’s memory and run a small personal project, but not much more. As of this review the company has not published paid pricing, so anyone planning to scale past the free limits is buying into an unknown future bill.

Compared to the alternatives, that lack of published pricing is the weak spot. Mem0 and Zep both have clear tiered plans for agent memory, and Supabase gives you a far larger free Postgres if you are willing to do the database work yourself. pumaDB is betting that the convenience of zero setup is worth more than a known price. For a hobby project that bet is fine. For anything you plan to grow, the missing pricing page is a real reason to hesitate.

Who is pumaDB best for?

Use pumaDB if you are a developer prototyping an AI agent and you want persistent memory today without provisioning infrastructure. The MCP integration means you can give a Claude or ChatGPT agent durable memory in minutes, which is great for demos, internal tools, and side projects.

Skip pumaDB if you are building something that needs to scale or store real volume. The 25 MB free cap is tiny, the paid pricing is unknown, and there is no public information about the team behind it, which is a trust concern when you are handing over your data. If you need production-grade memory with a clear price and a known vendor, look at Mem0 or Zep, or just run your own store.

There is also a security angle worth thinking through before you pour anything sensitive in. Agent memory often ends up holding user details, internal notes, or credentials that the agent picked up along the way. With no published information about where data is stored, how it is encrypted, or who operates the service, pumaDB is fine for non-sensitive scratch data but not somewhere to keep anything you would mind leaking. Treat the free tier as a sandbox, not a vault, until the company publishes more about its operations.

Best pumaDB alternatives

Mem0. A popular open-source and hosted memory layer for AI agents with published pricing and a large community. More mature than pumaDB, with a free tier and clear paid plans. The default choice if you want agent memory with a track record.

Zep. Memory built specifically for conversational agents, with strong recall and a hosted service. Pick it if your agent is chat-heavy and needs long-term conversation memory rather than general JSON storage.

Supabase. A full hosted Postgres with a generous free tier. More setup than pumaDB, but you get a real database, clear pricing, and no storage anxiety. Best when you want control and room to grow.

Final verdict: Is pumaDB worth it?

pumaDB nails a specific job. If you want to give an AI agent memory in the next ten minutes without touching a database, the MCP integration and the free tier make that trivially easy. The version history and rate limiting show real thought about how agents actually fail, and the narrow scope is a feature, not a flaw.

But it is early, and it shows. No published paid pricing, tiny free limits, and no visible team make it hard to recommend for anything beyond prototypes and personal projects. Use it to learn, to demo, and to scratch an itch. Just do not build a business on it until the pricing and the company behind it are out in the open. For now it is a promising tool worth bookmarking rather than betting on.