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web-meta-ai

❖ Communityv0.1.0

Meta web search — routes web_search through the server-side web_search tool on Meta's Responses API (Muse Spark); search-only.

Open in Hermes Desktop
hermes plugins install web-meta-ai

What it adds

Environment variables it needs 1

MODEL_API_KEY

README

From the reviewed commit 302cc18 ↗; it updates when the author re-pins.

hermes-web-meta-ai

A Hermes Agent web search backend that runs Hermes' web_search tool through the server-side web_search built-in on Meta's Responses API (Muse Spark). Muse Spark searches and opens pages on Meta's side, then returns structured {title, url, description} rows, so results look the same as Tavily, Exa or any other Hermes web provider.

It is search-only. web_extract keeps whatever extract backend you already use.

It follows the bundled xAI web backend (plugins/web/xai), but uses only the public agent.web_search_provider plugin surface. No core changes are needed.

Install

Requires Hermes Agent >= 0.21.3 (tested on 0.21.3 and 0.21.5).

hermes plugins install ajaynomics/hermes-web-meta-ai --enable

Or copy this directory to $HERMES_HOME/plugins/web-meta-ai/ and run hermes plugins enable web-meta-ai. Plugins are per profile: install and enable it in every profile that should use it.

Configure

web:
  search_backend: meta-ai        # search only
  meta-ai:                       # all optional
    model: muse-spark-1.3        # any Muse Spark model your key can use
    base_url: https://api.meta.ai/v1
    timeout: 120                 # seconds

Auth uses the same env vars as Hermes' bundled meta-ai model provider: MODEL_API_KEY (or META_API_KEY / META_MODEL_API_KEY). META_BASE_URL overrides the base URL.

If the plugin is not loaded, Hermes' resolver ignores search_backend: meta-ai and falls back to its normal provider walk.

Cost and latency

Each search is one extra Responses call. Meta bills web search per query, on top of tokens. In testing, a search took about 20–30 s and used 15–35k input tokens, because Muse Spark opens pages to check its results.

Trust model

Like the xAI backend, the model writes the titles and descriptions and chooses the URLs, and the query text can steer it. Treat returned URLs as model-generated links.

Tests

From a Hermes install (the Docker image works):

PYTHONPATH=/opt/hermes python -m unittest discover -s tests -v

License

MIT

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