New: the hosted MCP server is live. Connect your agent in one command.Read the docs →
StackResolve logoStackResolve

Compare

Autorev vs Stream

Autorev scores higher on the AgentReady, 80/100 against 43/100. They differ on 17 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Autorev. AutoRev is an AI coworker for service businesses that answers every call, books every job, and follows up so nothing slips.

Stream. Stream provides APIs and SDKs for building in-app chat, activity feeds, video, audio, and moderation.

Where Autorev is ahead

Autorev passes search discoverable, and Stream does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: structured api reference, openapi / spec quality, pricing understandable, request examples provided, response examples provided and errors and status codes documented. Stream misses those.

And on adopt, programmatic credential creation and free trial or free allowance. Stream misses those.

Finally, on operate, structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable and agent compatibility verified. Stream misses those.

Where Stream is ahead

Stream passes official python sdk and cli available, and Autorev does not. That is adopt, whether an agent can get a key and make its first successful call without a human in the loop.

What neither does

Both fail llms-full.txt / full agent docs, mcp discoverable, self-service signup, no mandatory sales call, fast time to first request, mcp integration available. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover. Autorev leads 80 to 67. Autorev misses llms-full.txt / full agent docs, mcp discoverable; Stream misses search discoverable, llms-full.txt / full agent docs, mcp discoverable.

Understand is whether an agent can read the docs and work out how the API behaves before calling it. Autorev leads 100 to 31. Autorev misses nothing; Stream misses structured api reference, openapi / spec quality, pricing understandable, request examples provided, response examples provided, errors and status codes documented.

Adopt. Both sit at 40/100 here. Autorev misses self-service signup, no mandatory sales call, fast time to first request, official python sdk, cli available, mcp integration available; Stream misses self-service signup, no mandatory sales call, programmatic credential creation, free trial or free allowance, fast time to first request, mcp integration available.

Operate. Autorev leads 100 to 35. Autorev misses nothing; Stream misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

Autorev does not publish a machine-readable starting price and has a free tier. Stream does not publish one.

Signal by signal

SignalAutorevStream
AgentReady8043
Discovery8067
Understanding10031
Adoption4040
Operability10035
Public APIYesYes
MCP serverNoUnknown
OpenAPI specYesUnknown
CLINoYes
llms.txtYesYes
Self-serve signupNoUnknown
Free tierYesUnknown

Which to pick

Autorev clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Autorev and Stream. Alternatives to each: Autorev, Stream.

An agent can fetch this as data: POST /v1/compare {"slugs": ["autorev", "getstream"]}