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The Meta API uses the OpenAI-compatible Responses API (POST /v1/responses) for the Muse Spark reasoning models. OpenClaw provides Meta as an official external plugin.

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Getting started

1

Install the plugin

2

Set the API key

3

Verify models are available

Lists the static Muse Spark catalog entries. If MODEL_API_KEY is unresolved, openclaw models status --json reports the missing credential under auth.unusableProfiles.

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Non-interactive setup

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Built-in catalog

Prices and data-use terms come from Meta’s pricing and rate limits documentation.
Meta’s pricing documentation and Terms of Service distinguish Standard Services from Contributor/Discounted Services:
  • Standard Services are the default. Meta says prompts and completions submitted to Standard Services are not used to train Meta models.
  • By using Contributor/Discounted Services, you permit Meta to use Content submitted to and generated by those services as described in the Terms. Under the Terms, use of Discounted Services acknowledges that permission. You must not submit sensitive, confidential, or personal information to the Discounted Services.
Meta’s Geographic Use Policy governs availability. It limits API access in some jurisdictions and adds end-user deployment restrictions for products built with the Contributor/Discounted model; those additional restrictions do not apply to your own use or products built with Standard Services.
Capabilities:
  • Text and image input through OpenClaw
  • Tool calling and streaming
  • Reasoning effort: minimal, low, medium, high, xhigh (OpenClaw default: high)
  • Stateless encrypted reasoning replay (store: false, include: ["reasoning.encrypted_content"])
Meta’s model catalog lists text, image, video, audio, and PDF input for these models. OpenClaw’s model catalog directly represents text and image input only; the other upstream modalities are not model-manifest input values. OpenClaw explicitly selects high when no thinking level is configured. This is an OpenClaw default, not Meta’s omitted-parameter behavior: Meta’s reasoning documentation says that when reasoning.effort is omitted, the model reasons at a model-determined level.
Muse Spark does not accept reasoning.effort: "none". OpenClaw maps --thinking off to minimal for this provider.

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Manual config

If the Gateway runs as a daemon (launchd, systemd, Docker), make sure MODEL_API_KEY is available to that process — for example in ~/.openclaw/.env or through env.shellEnv. A key exported only in an interactive shell will not help a managed service unless the env is imported separately.

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Smoke test

The live suite exercises enabled Meta cases against POST /v1/responses.

Model providers

Choosing providers, model refs, and failover behavior.

Thinking modes

Reasoning effort levels for Muse Spark.

Configuration reference

Agent defaults and model configuration.