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Arcade vs Glama

Arcade scores higher on the AgentReady, 61/100 against 56/100. They differ on 13 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Arcade. The runtime between your agents and every system they need to reach.

Glama. Glama is a superset of the official MCP Registry that indexes, scans, and ranks MCP servers based on security, compatibility, and ease of use.

Where Arcade is ahead

Arcade passes public docs discoverable and llms-full.txt / full agent docs, and Glama does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: authentication documented. Glama misses it.

And on adopt, agent-compatible signup flow, fast time to first request, copyable quickstart, official python sdk and cli available. Glama misses those.

Where Glama is ahead

Glama passes pricing understandable and limits / constraints documented, and Arcade does not. That is understand, whether an agent can read the docs and work out how the API behaves before calling it.

It also holds adopt: no mandatory sales call and free trial or free allowance. Arcade misses those.

And on operate, structured, predictable output. Arcade misses it.

What neither does

Both fail clear product positioning, structured api reference, openapi / spec quality, request examples provided, response examples provided, errors and status codes documented, programmatic credential creation, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable. 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 is whether an agent can find the product at all without being told it exists. Arcade leads 87 to 67. Arcade misses clear product positioning; Glama misses clear product positioning, public docs discoverable, llms-full.txt / full agent docs.

Understand. Glama leads 31 to 23. Arcade misses structured api reference, openapi / spec quality, pricing understandable, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Glama misses structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented.

Adopt. Arcade leads 76 to 57. Arcade misses no mandatory sales call, programmatic credential creation, free trial or free allowance; Glama misses agent-compatible signup flow, programmatic credential creation, fast time to first request, copyable quickstart, official python sdk, cli available.

Operate. Glama leads 67 to 56. Arcade misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable; Glama misses machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable.

Pricing

Arcade does not publish a machine-readable starting price. Glama starts at $9/month and has a free tier.

Signal by signal

Which to pick

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

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