The long-term memory layer for AI agents, focused on integrations, context, and durable memory workflows.
CortexDB
CortexDB is the long-term memory layer for AI agents.
It helps teams give agents and AI applications durable memory, connected context, and practical ways to integrate memory into real workflows.
Whether you are building an internal copilot, a support assistant, an engineering knowledge layer, or a companion-style application, CortexDB is designed to help memory become a first-class part of the product.
Why CortexDB?
AI systems often struggle with continuity. They lose context between sessions, forget important prior decisions, and cannot easily draw from the full working memory of a team, product, or organization.
Teams use CortexDB when they want to:
- give agents durable memory beyond a single conversation
- connect knowledge across tools like Slack, GitHub, and Jira
- provide richer context to workflows, copilots, and assistants
- support multi-tenant and enterprise use cases
- make memory accessible through SDKs, APIs, and MCP-compatible tools
Key Advantages
Built for AI memory
CortexDB is designed around memory workflows such as storing context, retrieving it later, and connecting related information across sessions.
Integration ready
Use CortexDB with popular agent frameworks, SDKs, connectors, and MCP-compatible tools.
Connected context
CortexDB helps applications work with relationships, history, and related context instead of isolated text fragments.
Operational workflows
Support developer tools, support workflows, research assistants, copilots, and customer-facing AI products from one memory layer.
Multi-tenant and governed
Organize memory by tenant, team, or application and support enterprise operational requirements.
Cloud platform
Get started quickly with the CortexDB cloud platform, designed for production workloads from day one.
How CortexDB fits into your stack
At a high level, CortexDB sits between your applications and the knowledge they need to retain and retrieve.
It commonly works with:
- application events and user interactions
- chat, ticketing, and collaboration systems
- code and engineering systems
- agent frameworks and orchestration layers
- APIs, SDKs, and MCP-based tool environments
How It Works
Connect
Connect CortexDB to your app, framework, or workflow using SDKs, APIs, connectors, or MCP.
Capture
Store the interactions, events, documents, and decisions your AI system should be able to remember later.
Retrieve
Retrieve relevant context during prompts, workflows, agent runs, and user interactions.
Operate
Use CortexDB as part of production AI systems that need persistent memory, cross-tool context, and enterprise-ready workflows.
Integrations and plugins
CortexDB ships 31 integration recipes and 16 managed connectors across the AI ecosystem. Inference backend guides are deployment configuration pages for self-hosted and enterprise deployments, not adoption integrations.
Agent Frameworks (22)
LangChain · LangGraph · LlamaIndex · CrewAI · AG2 (AutoGen) · AutoGen · Agno · DSPy · Smolagents · CAMEL-AI · PydanticAI · OpenAI Agents · Google ADK · Letta · BeeAI · NeMo Guardrails · Instructor · ControlFlow · Eliza OS · Hermes · OpenClaw · Mastra
Orchestration (6)
Temporal · n8n · Prefect · Airflow · Zapier · Make.com
No-Code Platforms (3)
Vercel AI SDK · Flowise · Dify
Inference Backends (6)
Ollama · Groq · Together AI · Fireworks AI · vLLM · DeepInfra
Data Connectors (16)
Slack · GitHub · GitLab · Jira · Linear · Confluence · Notion · PagerDuty · Discord · Microsoft Teams · Google Workspace · Salesforce · HubSpot · Zendesk · Intercom · ServiceNow
Access Surfaces
| Artifact | Install package / command | Import or executable |
|---|---|---|
| Python SDK | pip install cortexdbai | from cortexdb.v1 import V1Client |
| TypeScript SDK | npm install cortexdbai | import { V1Client } from "cortexdbai/v1" |
| CLI | pip install cortexdb-cli | cortexdb |
| MCP server | pip install cortexdb-mcp | cortexdb-mcp |
| REST API | none | https://api-v1.cortexdb.ai |
The install package names are intentionally artifact-specific. Use cortexdbai for the SDKs, cortexdb-cli for the CLI, and cortexdb-mcp for MCP clients.
Quick Example
import requests
from cortexdb.v1 import V1Client
# 1. Mint a v1 token (one-shot signup — no email, no card)
r = requests.post("https://api-v1.cortexdb.ai/v1/auth/signup", json={}).json()
token, user_id, scope = r["token"], r["user_id"], r["scope"]
# 2. Open a client
client = V1Client(
api_url="https://api-v1.cortexdb.ai",
actor=user_id,
bearer=token,
)
# 3. Capture an experience
client.experience(
scope=scope,
text="We decided to migrate from PostgreSQL to CockroachDB for the payments service. Timeline is Q2 2026.",
observed_at="2026-05-16T10:42:00Z",
idempotency_key="decision-payments-001",
)
# 4. Recall a stratified pack (events + episodes + facts + beliefs + understanding)
pack = client.recall(
scope=scope,
query="What database are we using for payments?",
view="holistic",
include=["events", "beliefs", "facts", "episodes"],
)
print(pack.get("context_block", ""))