Infino AI MCP Server

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

claude mcp add mcp-server -- npx -y @infino-ai/mcp-server

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

[mcp_servers.mcp-server]
command = "npx"
args = ["-y", "@infino-ai/mcp-server"]

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

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

This one needs environment variables set before it will start: 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.). The author declared them in the registry entry; get the values from the project itself.