Hasura Alternative for REST, GraphQL and MCP APIs
The best Hasura alternative depends on who calls your API. If apps, partners and AI agents all need access, a generated API that gives you REST, GraphQL and an MCP server from one definition, with hosting, keys and logs, is the closer fit. If your team works in GraphQL on Postgres, Hasura stays a strong choice.
Why teams look for a Hasura alternative
Hasura points at a database and gives you a GraphQL API with role based permissions in an afternoon. That is why many teams adopt it. The search for an alternative usually starts later, for practical reasons. A partner wants plain REST and an OpenAPI file. A customer success tool cannot speak GraphQL. An agent needs a handful of named tools, not a query language it can misuse. Or somebody has to run, upgrade and monitor the engine, and nobody wants that job.
What Hasura does well
Be fair about it. Hasura has a mature permission system with row and column rules per role, a console for modeling relationships, subscriptions, remote schemas that stitch other services into one graph, and event triggers. If the main consumer is a React or mobile client written by your own team, and your data lives in Postgres, it is a sound pick that many teams run for years.
Where teams outgrow it
- The center of gravity is GraphQL. Consumers that expect REST, an OpenAPI file and a docs page need extra work.
- AI agents work better with a few named tools than with an open query language. Exposing a whole graph to a model invites expensive or over broad queries.
- Running it yourself means upgrades, scaling, secrets and monitoring. Hosted offers move that work, at a price that depends on the plan you choose.
- Per customer keys, quotas and a call log you can hand to a security reviewer are not the default shape of the product.
- Your source is not always Postgres. A spreadsheet, a MySQL database or an OpenAPI file from another team may be the real starting point.
What to require from the replacement
Write the list before you compare products. Which outputs do consumers need: REST, GraphQL, MCP. Which sources do you have. Who hosts it. How are keys, rate limits and row rules attached. Can you export the code if you leave. How do you see who called what.
The options compared
| Option | Best at | Outputs | Hosting | Keys and logs | Best for |
|---|---|---|---|---|---|
| Hasura | GraphQL on Postgres with fine grained roles | GraphQL, REST from saved queries | Self run or hosted | Roles and your own logging | Teams building GraphQL clients |
| PostgREST | Thin REST layer over Postgres | REST | You run it | You build it | Engineers who like to wire parts together |
| Hand built API | Exact fit | Whatever you write | You run it | You build it | Teams with spare engineers |
| Generated API (APIGenerator) | One definition, several outputs | REST, GraphQL, MCP, OpenAPI | Managed or exported code | Per key limits and call log | Teams serving apps, partners and agents |
Hasura wins when GraphQL is the product and the database is Postgres. A generated API wins when the same data must reach a REST client, a GraphQL client and an agent without three projects.
How the move looks in practice
- Export your schema or collect the tables and views your consumers actually use. Many teams find the list is shorter than the graph.
- Upload it, or describe it in plain words, and review the proposed endpoints and tools. See the database to API page for the flow.
- Check each Hasura permission you rely on and re-create it as a row rule on a key.
- Run the new API next to the old one for a week and compare responses.
- Point REST consumers at the new endpoints and agents at the MCP server. The graphql api generator page covers keeping a GraphQL endpoint for clients that need one. If you are weighing a thinner REST layer instead, read the PostgREST alternative article.
What changes for AI agents
An agent talking to a graph can write any query the schema allows. An MCP server built from the same definition gives it named tools with typed arguments, a page size cap and a log line per call. The postgres mcp server page explains how row rules attach to a key. Schema drift is the quiet risk in either setup, and a tool such as data observability that watches freshness and schema changes helps you notice when a column your consumers rely on moves.
Cost and when it pays off
Count the engineer hours spent on upgrades and on custom REST wrappers, then compare them with a flat plan, see pricing. The switch pays off when you have more than one kind of consumer, or when nobody on the team wants to operate the engine.