MCP Server MCP

io.github.infino-ai/mcp-server

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Keyword, vector, hybrid, and SQL retrieval over data on object storage, for AI agents.

Homepage Verified source GitHub

Install

npx -y @infino-ai/[email protected]

Configuration Example

{
  "remotes": [],
  "packages": [
    {
      "registryType": "npm",
      "identifier": "@infino-ai/mcp-server",
      "version": "0.10.2",
      "transport": {
        "type": "stdio"
      },
      "environmentVariables": [
        {
          "description": "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.",
          "format": "string",
          "name": "INFINO_MCP_URI"
        },
        {
          "description": "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.",
          "format": "string",
          "name": "INFINO_API_KEY"
        },
        {
          "description": "Set (1/true/yes) to expose add/update/delete tools and allow DDL/DML through SQL. Read-only when unset.",
          "format": "string",
          "name": "INFINO_MCP_ENABLE_WRITES"
        },
        {
          "description": "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.",
          "format": "string",
          "name": "INFINO_MCP_EMBED_PROVIDER"
        },
        {
          "description": "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.",
          "format": "string",
          "name": "INFINO_MCP_EMBED_BASE_URL"
        },
        {
          "description": "API key for the 'openai' provider. Sent as both Authorization: Bearer and api-key so one value works for OpenAI and Azure OpenAI.",
          "format": "string",
          "name": "INFINO_MCP_EMBED_API_KEY"
        },
        {
          "description": "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.",
          "format": "string",
          "name": "INFINO_MCP_EMBED_MODEL"
        },
        {
          "description": "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.",
          "format": "string",
          "name": "INFINO_MCP_VALIDATE"
        }
      ]
    }
  ]
}

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