Singlebase documentation

Give your agents a data foundation.

Singlebase is a backend platform for applications and AI agents. It brings your data, files, users, and AI together through one JSON API.

>_Make your first requestConnect a project and use the REST API from your backend.{ }Connect an agentGive an agent access to the collections and operations it needs.

One platform, shared context

Singlebase provides a JSON document database with VectorDB embeddings, vector search, FTS5 full-text search, and hybrid retrieval, plus file storage, user authentication and account management, AI generation and embeddings, and chat with retrieval from your knowledge sources. Your application and agents use these services through the same API, with access controlled by API keys and user permissions.

Database

Store JSON documents, compute totals, and find context with VectorDB embeddings, vector search, FTS5 full-text search, and hybrid retrieval.

DocumentDB reference →

Agents & retrieval

Scope agent keys by collection and operation, or connect over MCP. Ground chat answers in named docsets using vector, FTS5 keyword, or hybrid retrieval with access rules.

Agent access → · MCP → · Docsets →

Intelligence

Generate and summarize content, extract structured JSON, create embeddings, and keep conversations.

LLM reference → · Chat reference →

Identity & storage

Sign users in, manage their accounts, upload files, and convert documents to Markdown.

Authentication → · Files →

One endpoint, one request shape

Send a POST request to your project's endpoint with X-API-KEY and a JSON body:

{
  "operation": "data.query",
  "payload": {
    "collection": "product_catalog",
    "filter": { "category": "bags" },
    "per_page": 5
  }
}

Use a server key from your backend, or an agent key with read permission on product_catalog. A web key needs a signed-in user's bearer token for this query and returns that user's documents. See API keys and access.

Choose your next step

• Quickstart: create a document and query it from server code.
• API overview: request headers, key types, responses, errors, and batches.
• API reference: operations grouped by service.
• JavaScript SDK: connect with sbc.data, sbc.llm, and sbc.chat; see the quickstart for JavaScript and Python.
• Data and Query syntax: find and update your records.
• Agents: give an agent its own scoped access.
• MCP: connect agent runtimes with scoped discovery, document tools, and answers with sources.
• Conversation: use knowledge sources, attachments, and persisted chats.
• LLM: generate text, extract JSON, and create embeddings.
• Authentication, Users, and Files: build the application around your data.

Documentation for AI tools

Use llms.txt for a compact reading guide, llms-full.txt for the complete reference, or the Markdown link on each page for its plain-text source. Examples use placeholders and illustrative values; resource names must exist in your project.