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+300% YoY search growth · $52 CPC keyword

AI Agent Database
Persistent memory, vector search, and self-provisioning for agents.

Give your agents a database they can provision themselves. No human signup required. ZeroDB spins up in under 2 seconds — so your agents remember everything, forever.

<2s
Provision time
69
MCP tools
0
Human steps
Deploy Agent Database →See the API
The Problem

86% of agents use ephemeral storage.
Every restart is amnesia.

Most agent frameworks default to in-memory context windows. Your agent processes a request, produces an output, and then forgets everything. The next session starts blank. It cannot remember that a user prefers Python over JavaScript, that a bug was filed last week, or that a customer called three times about the same issue.

The industry calls this the stateless agent problem. It is not a model capability issue — it is an infrastructure issue. The models are capable of reasoning about stored context. The problem is that nobody gave them a place to store it that they can access autonomously.

Traditional databases are not the answer either. Postgres, Supabase, Pinecone — they all require a human to sign up, provision credentials, and configure access. An autonomous agent cannot complete an OAuth flow. It cannot click through a dashboard. It needs a database it can provision by itself, in real time, with a single API call.

86%
of production agents use ephemeral storage
No persistent memory between sessions
12×
more user sessions needed to re-establish context
Wasted tokens and degraded UX
0
traditional databases support agent self-provisioning
All require human OAuth or dashboard signup
Zero-Auth Provisioning

Agents provision their own database in <2 seconds

One POST request. No OAuth. No email. No dashboard. Your agent gets a live database with an API key and project ID — instantly.

Agent self-provisions a database
# Agent provisions its own database — no human required
import httpx

response = httpx.post(
    "https://api.ainative.studio/api/v1/public/instant-db",
    json={"agent_id": "support-agent-v2", "tier": "starter"},
    # No Authorization header — this endpoint is agent-accessible
)

db = response.json()
# {
#   "project_id": "proj_8f3k2m",
#   "api_key":    "zdb_live_...",
#   "endpoint":   "https://api.zerodb.io/v1",
#   "provisioned_in_ms": 1_847,
#   "storage_gb": 10,
#   "vector_dims": 1536
# }

# Agent now has a full database — vectors, memory, NoSQL, files
print(f"Database ready in {db['provisioned_in_ms']}ms")

Provisioning comparison

StepSupabase / Pinecone(30s+ · OAuth required)ZeroDB(<2s · zero auth)
Open dashboardRequired — agent cannot do thisNot needed
OAuth / email signupRequired — blocks autonomous agentsNot needed
Create projectClick through UI wizardIncluded in POST /instant-db
Get API keyCopy from dashboard settingsReturned in API response
Start using30–120 seconds, human required<2 seconds, fully autonomous
Agent Memory API

Cognitive memory, not just storage

Six primitives that mirror how human memory works — not a key-value store bolted onto a vector index, but a complete memory system designed from first principles for AI agents.

🧠
.remember()

Store a fact, observation, or experience with semantic indexing

🔍
.recall()

Retrieve memories by semantic similarity — not just exact key match

🗑
.forget()

Delete a specific memory — supports GDPR / right-to-be-forgotten

💭
.reflect()

Synthesize a narrative summary from a collection of memories

🔗
.relate()

Link entities in a context graph — people, topics, events, documents

👤
.profile()

Get a structured summary of a person, project, or topic from memory

Python · Agent Memory API
from zerodb import ZeroDB

db = ZeroDB(api_key="zdb_live_...", project_id="proj_8f3k2m")

# Store a memory
db.memory.remember(
    agent_id="support-agent-v2",
    content="User prefers Python SDK over REST API. Mentioned 3 times.",
    metadata={"user_id": "usr_4829", "confidence": 0.95},
)

# Recall semantically — not just keyword match
memories = db.memory.recall(
    agent_id="support-agent-v2",
    query="what does this user prefer?",
    limit=5,
)

# Reflect — synthesize a narrative from memories
profile = db.memory.reflect(
    agent_id="support-agent-v2",
    subject="usr_4829",
)
# → "User is a Python developer who has contacted support 3 times about
#    the SDK. They prefer async patterns and have not yet tried the MCP tools."
TypeScript · Agent Memory API
import { ZeroDB } from '@zerodb/client';

const db = new ZeroDB({ apiKey: 'zdb_live_...', projectId: 'proj_8f3k2m' });

// Store an observation after each conversation turn
await db.memory.remember({
  agentId: 'coding-assistant',
  content: 'User is refactoring a Next.js 14 app to use the App Router.',
  metadata: { repoUrl: 'github.com/user/myapp', language: 'TypeScript' },
});

// Retrieve context before generating a response
const context = await db.memory.recall({
  agentId: 'coding-assistant',
  query: 'what framework is the user working with?',
  limit: 10,
});

// Profile — structured summary for system prompt injection
const userProfile = await db.memory.profile({
  agentId: 'coding-assistant',
  subject: 'user_session_8472',
});
console.log(userProfile.summary);
// → "TypeScript developer migrating a production Next.js app to App Router.
//    Prefers functional components. Has asked about server actions 4 times."
69 MCP Tools

Agents interact via MCP, not REST

ZeroDB exposes its entire surface area as MCP tools. No REST calls, no SDK installation, no credentials in config files. Agents pick up the tools automatically when they connect to the MCP server.

Compatible with Claude Code, Cursor, and Windsurf out of the box.

Vector Search

12 tools
  • zerodb_vector_upsert
  • zerodb_vector_search
  • zerodb_vector_list
  • zerodb_vector_stats
  • + more...

Memory

8 tools
  • zerodb_store_memory
  • zerodb_search_memory
  • zerodb_get_context
  • zerodb_synthesize_context
  • + more...

NoSQL Tables

10 tools
  • zerodb_table_create
  • zerodb_table_insert
  • zerodb_table_query
  • zerodb_table_update
  • + more...

File Storage

6 tools
  • zerodb_file_upload
  • zerodb_file_download
  • zerodb_file_list
  • zerodb_file_url
  • + more...

Event Streams

5 tools
  • zerodb_event_create
  • zerodb_event_list
  • zerodb_event_subscribe
  • zerodb_event_replay
  • + more...

Context Graphs

15 tools
  • zerodb_graph_entity
  • zerodb_graph_edge
  • zerodb_graph_traverse
  • zerodb_graphrag
  • + more...
~/.claude/settings.json · Add ZeroDB MCP to Claude Code
{
  "mcpServers": {
    "zerodb": {
      "command": "npx",
      "args": ["-y", "ainative-zerodb-memory-mcp"],
      "env": {
        "ZERODB_API_KEY": "zdb_live_...",
        "ZERODB_PROJECT_ID": "proj_8f3k2m"
      }
    }
  }
}

// Claude Code now has 69 ZeroDB tools available automatically.
// Agent can call zerodb_store_memory, zerodb_vector_search, etc.
// without any REST calls or SDK imports.
Agent Discoverability

Agents find your database automatically

ZeroDB publishes machine-readable discovery files so agents can find your database without being explicitly configured — like robots.txt, but for AI agents.

.well-known/mcp.jsonMCP server discovery

Tells any MCP-compatible agent where your database endpoint is, what tools it exposes, and how to authenticate. Agents read this file automatically when visiting your domain.

{
  "mcp_endpoint": "https://api.zerodb.io/mcp",
  "version": "1.0",
  "tools": ["zerodb_vector_search", "zerodb_store_memory", ...],
  "auth": { "type": "api_key", "header": "X-ZeroDB-Key" }
}
.well-known/agent.jsonMachine-readable API spec

A structured description of your API capabilities, rate limits, pricing, and data schema — written for agents to parse, not humans to read.

{
  "name": "ZeroDB",
  "capabilities": ["vectors", "memory", "nosql", "files"],
  "rate_limits": { "requests_per_minute": 1000 },
  "provisioning": {
    "endpoint": "/api/v1/public/instant-db",
    "auth_required": false
  }
}

The future: fully autonomous agent infrastructure

With discovery files in place, an agent visiting your domain can find your database, read its capabilities, provision its own access credentials, and start storing memory — all without a single line of hardcoded configuration. This is the architecture that enables truly autonomous multi-agent systems.

Who uses an AI agent database

Any agent that needs to remember context across sessions — which is most production agents.

💻

AI coding assistants

Remembers your codebase architecture, preferred patterns, recent refactors, and open bugs. Your coding agent gets better every session instead of starting blank.

  • ✓Codebase structure
  • ✓Language & framework preferences
  • ✓Open issues and TODOs
  • ✓Past solutions to recurring errors
🎧

Customer support agents

Maintains full conversation history, customer preferences, and resolution patterns across sessions. No more asking customers to repeat themselves.

  • ✓Full conversation history
  • ✓Customer preferences and tone
  • ✓Previous resolutions
  • ✓Escalation patterns
🔬

Research agents

Accumulates knowledge from every search, paper read, and synthesis pass. Builds a private knowledge graph that grows richer with every task.

  • ✓Research findings
  • ✓Source credibility scores
  • ✓Topic relationships
  • ✓Knowledge gaps
📊

Sales agents

Carries full CRM context — deal history, stakeholder preferences, objection patterns, and pipeline stage — into every interaction.

  • ✓Deal history and notes
  • ✓Stakeholder communication styles
  • ✓Objections and responses
  • ✓Follow-up timing patterns

Frequently Asked Questions

What is an AI agent database?

An AI agent database is a storage layer designed for autonomous agents rather than humans. Unlike traditional databases that require a human to sign up, provision credentials, and configure access, an AI agent database can be provisioned by the agent itself via API — no OAuth flow, no signup page, no human in the loop. It combines vectors for semantic search, structured records, files, and event logs in a format that agents can read and write efficiently using MCP tools.

How is ZeroDB different from Supabase or Pinecone for agents?

Supabase and Pinecone require human signup via OAuth or a web dashboard — an agent cannot complete these flows autonomously. ZeroDB is the only database that agents can provision themselves in under 2 seconds via a single unauthenticated API call. Beyond provisioning, ZeroDB combines vectors, memory, NoSQL, files, and MCP tools in one service — eliminating the need to stitch together Pinecone (vectors), Redis (cache), S3 (files), and a separate memory layer.

What is AI agent memory and how does it work?

AI agent memory works by storing observations, facts, and context as semantically indexed records that agents can retrieve in future sessions. ZeroDB's memory API uses six cognitive primitives: remember (store a fact), recall (retrieve by semantic similarity), forget (delete a memory), reflect (synthesize a profile from memories), relate (link entities), and profile (get a structured summary of a person or topic). This mirrors how human memory works — not just key-value storage, but associative, semantic, and reflective.

What is zero-auth provisioning?

Zero-auth provisioning means an agent can create its own database instance with a single API call — no OAuth redirect, no email verification, no human approval required. The agent POSTs to /api/v1/public/instant-db and receives an API key and project ID in under 2 seconds. This is critical for autonomous agent workflows where no human can be present to complete a signup flow.

Does ZeroDB work with Claude Code, Cursor, and Windsurf?

Yes. ZeroDB publishes an npm MCP server package (ainative-zerodb-memory-mcp) that adds 69 tools to any MCP-compatible client. Add it to your ~/.claude/settings.json, .cursor/mcp.json, or Windsurf settings with your API key, and all ZeroDB tools are immediately available to your agents — no REST calls, no SDK imports required.

What is the "ai native database" trend?

"AI native database" refers to databases designed from the ground up for AI agent workloads rather than adapted from human-centric systems. Key characteristics: support for high-dimensional vector embeddings, semantic search by default, agent-accessible provisioning APIs, MCP tool integration, and memory primitives beyond simple CRUD. Search interest in "ai native database" grew 300% year-over-year as teams realized that traditional databases create a bottleneck in autonomous agent pipelines.

Live in under 2 seconds

Deploy an Agent Database in 2 Seconds

One API call. Your agent gets persistent memory, vector search, 69 MCP tools, and self-provisioning. No human signup. No OAuth flow. No dashboard.

Deploy ZeroDB Free →Read the Docs

Continue Learning

ZeroDB

Product

The AI-native database — vectors, memory, NoSQL, files, and 69 MCP tools in one service.

Agent Orchestration

Use Case

Deploy multi-agent systems that coordinate specialized agents to complete complex tasks.

Agent Memory API

Product

ZeroMemory cognitive memory system — remember, recall, reflect, relate, profile.

What is MCP?

Guide

The complete guide to Model Context Protocol — how agents connect to tools and databases.