{"servers":[{"server":{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"io.github.infino-ai/mcp-server","description":"Keyword, vector, hybrid, and SQL retrieval over data on object storage, for AI agents.","repository":{"url":"https://github.com/infino-ai/infino-mcp","source":"github"},"version":"0.10.2","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"}]}]},"_meta":{"io.modelcontextprotocol.registry/official":{"status":"active","statusChangedAt":"2026-08-24T08:56:14.548907Z","publishedAt":"2026-08-24T08:56:14.548907Z","updatedAt":"2026-08-24T08:56:14.548907Z","isLatest":true}}}],"metadata":{"count":1}}