infino-mcp

Package (npm 0.18.0)

npx -y @infino-ai/[email protected]

Or add to your MCP client config:

{
  "mcpServers": {
    "infino-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@infino-ai/[email protected]"
      ]
    }
  }
}

• INFINO_MCP_URI — Data to serve: a local path, an s3://|az:// bucket URI, or a hosted https://<host>/<database> endpoint (Infino Cloud). Optional — defaults to a durable per-user directory (~/.infino/mcp) so data persists across restarts, falling back to an ephemeral memory:// catalog only if that directory can't be created.
• INFINO_API_KEY — API key for a hosted (https://) Infino Cloud endpoint. Required when INFINO_MCP_URI is an https:// URI; ignored for local and object-storage connections.
• INFINO_MCP_EMBED_PROVIDER — Embedding provider: 'local' (Hugging Face transformers.js, default) or 'openai' (any OpenAI-compatible /embeddings endpoint, including Azure OpenAI's /openai/v1 surface). Inferred as 'openai' when INFINO_MCP_EMBED_BASE_URL is set.
• INFINO_MCP_EMBED_BASE_URL — Base URL of the OpenAI-compatible embeddings API (e.g. https://api.openai.com/v1 or https://<resource>.openai.azure.com/openai/v1). Required when the provider is 'openai'; the server POSTs to <base>/embeddings.
• INFINO_MCP_EMBED_API_KEY — API key for the 'openai' provider. Sent as both Authorization: Bearer and api-key so one value works for OpenAI and Azure OpenAI.
• INFINO_MCP_EMBED_MODEL — Embedding model. local: a Hugging Face feature-extraction model (default Xenova/all-MiniLM-L6-v2, 384-dim). openai: the model/deployment name (e.g. text-embedding-3-small, 1536-dim). Must match the model that produced the table's stored vectors.
• INFINO_MCP_VALIDATE — Set (1/true/yes) to probe the object store at startup, so bad credentials or an unreachable bucket fail then instead of on the first search.