Free web
Free source (opens in a new tab)
Month
For: Side projects
Limits
- 5 agents
- 5,000 memories
1 more
- 2,000 AI extractions
Includes
- Every feature
- Local SQLite or cloud sync
1 more
- Community support
CodingDocumented overviewLast checked Sep 29, 2026
Octopoda: Pricing, Features & Best Use Cases
Persistent memory layer for AI agents with versioning, sharing and monitoring, installed via pip.
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Our take: Octopoda is a good fit for developers and AI-first teams who need persistent, versioned, shareable memory for LangChain, CrewAI, MCP or custom agents, with an MIT open-source core and a free 5-agent tier.
Main limitation: Free is capped at 5 agents, 5,000 memories and 2,000 AI extractions, and cloud features require an account.
Who should use Octopoda
Octopoda is a good fit for developers and AI-first teams who need persistent, versioned, shareable memory for LangChain, CrewAI, MCP or custom agents, with an MIT open-source core and a free 5-agent tier. Based on the vendor's documentation, not on a hands-on test.
Best for: Developers building agents
Also a good fit for
- AI-first product teams
Consider another tool if free tier capped at 5 agents and 5,000 memories
Or if
- Pro capped at 25 agents
- Requires an account for cloud features
Octopoda pricing and usage limits
Prices checked Sep 29, 2026 on the official US pricing page. Official pricing ↗ Prices and limits change often.
Free access and trial conditions
Free tier, no card; open-source core
None separate
Paid plans: what changes as you upgrade
Pro web
$19/mo source (opens in a new tab)
Month
Yearly saves 20%
For: Individual developers
Limits
- 25 agents
- 250,000 memories
1 more
- 10,000 AI extractions
Includes
- Email support within 1 business day
- Priority bug fix queue
Business web
$49/mo source (opens in a new tab)
Month
Yearly saves 20%
For: Teams
Limits
- 75 agents
- 1,000,000 memories
1 more
- 50,000 AI extractions
Includes
- Priority support 4h
- Founder onboarding call
1 more
- 99.5% uptime SLA
Scale web
$99/mo source (opens in a new tab)
Month
Yearly saves 20%
For: AI-first teams
Limits
- Unlimited agents
- 5,000,000 memories
1 more
- Unlimited AI extractions
Includes
- Dedicated shared Slack channel
- 99.9% SLA
1 more
- Quarterly strategy review
Enterprise web
Custom pricing source (opens in a new tab)
Month
For: Large organizations
Includes
- VPC or on-prem
- Custom SLA
2 more
- SOC 2
- Dedicated engineer
Usage caps, credits and extra costs
None listed; hitting limits does not break writes
Not stated
What is Octopoda, and how does it work?
Octopoda gives AI agents memory that survives restarts. Agents can store, recall, version and share facts, with works-with notes for LangChain, CrewAI, MCP and other SDKs. A web dashboard shows agent health, operations and anomalies such as loops. Plans are priced by agent count, memory count and AI extractions.
What you provide and what you get back
You provide
- Agent facts written through the SDK or REST API
- Framework integrations such as LangChain or CrewAI
- MCP tool calls
You get back
- Recalled memories by key or meaning
- Version history, snapshots and rollbacks
- Dashboard health, anomalies and loop alerts
Where you can use it
- Platforms
- Web
- Account
- Required
- Agents
- 5 / 25 / 75 / unlimited
- Memories
- 5k / 250k / 1M / 5M
- License
- MIT core
- Interfaces
- Python SDK, REST, MCP (28 tools)
What people use Octopoda for
Scenarios are worked out by our editors from the documentation; the actual result depends on your input and plan.
Give support agents long-term user memory
- Who
- Developers building support copilots
- You provide
- Facts stored per user
- Expected result
- Agents recall context across sessions
- Plan needed
- Free (5 agents)
- Limitation
- Free capped at 5,000 memories source (opens in a new tab)
Share context between agents
- Who
- Teams running several agents
- You provide
- Shared memory space
- Expected result
- Agents read common context
- Plan needed
- All plans
- Limitation
- Agent limits by plan source (opens in a new tab)
Roll back agent state after errors
- Who
- Teams in production
- You provide
- Snapshots of memory
- Expected result
- Restored earlier state
- Plan needed
- All plans
- Limitation
- Memory capacity by plan source (opens in a new tab)
Octopoda features and their limits
Remember and recall by key or meaning
Stores facts and fetches them by exact key or semantic search Gives agents persistent context
Version history per key
Keeps earlier values of each memory Lets you audit changes
Snapshots and rollback
Captures agent memory state and restores it Recovers from bad runs
Shared memory spaces
Lets multiple agents read and write a common store Coordinates multi-agent work
Loop detection and circuit breakers
Spots runaway agent loops and stops them Saves token spend
Octopoda pros and cons
Reasons to choose Octopoda
- Free plan with no card required Full product at small scale documented source (opens in a new tab)
- Every plan includes the full product Paid tiers only add capacity and support documented source (opens in a new tab)
- MIT open-source core runs locally on SQLite You can self-host without cloud documented source (opens in a new tab)
- Docs for LangChain, CrewAI, AutoGen, OpenAI, Anthropic and MCP Covers common frameworks documented source (opens in a new tab)
- Flat monthly pricing, no per-seat fees Cost depends only on agents and memories documented source (opens in a new tab)
Check before paying for Octopoda
- Free tier capped at 5 agents and 5,000 memories Production fleets outgrow it documented source (opens in a new tab)
- Pro capped at 25 agents Larger fleets need Business at $49 documented source (opens in a new tab)
- Requires an account for cloud features Cloud sync and dashboard are not available offline documented source (opens in a new tab)
- Developer-oriented, needs code integration Not for non-technical users documented source (opens in a new tab)
- SOC 2 listed as in progress Compliance-bound teams must wait or use Enterprise documented source (opens in a new tab)
How to use Octopoda for adding persistent memory to an AI agent
Set up Octopoda
- Run pip install octopoda
- Sign up at octopodas.com for an API key (optional for local mode)
- Initialize Octopoda in your agent with two lines of code
- Choose your framework guide such as LangChain or CrewAI
Example: adding persistent memory to an AI agent
- Register an agent with its own identity
- Write a user preference as a memory
- Restart the agent and recall the memory
- Take a snapshot and roll back after a bad run
Review and export the result
- Confirm the memory survives a restart
- Check the dashboard for agent health and loop alerts
Octopoda integrations and API
Native integrations and export formats
Export: JSON via /v1/auth/export
API access and separate billing
Octopoda has no public API in its official documentation. REST API and webhooks documented API documentation ↗
Privacy, data use and commercial rights
Summarized from the vendor's current policies; this is not legal advice and a vendor's badge is not an independent audit.
How your inputs and outputs are handled
Agent memory stored locally in SQLite by default; cloud tier uses PostgreSQL with row-level security
Export or delete all data anytime via API
Controls for business users
- Hash-chained audit trail
- GDPR compliance stated
- SOC 2 in progress
Policies: octopodas.com/privacy
Other tools to consider instead of Octopoda
"Better suited" is based on documented features and pricing, not on a head-to-head test.
n8n: better suited to
GitHub Copilot: better suited to
Cursor: better suited to
| Alternative | When to choose it | Pricing | Limitation | |
|---|---|---|---|---|
| n8n | — | — | ||
| GitHub Copilot | — | — | Compare | |
| Cursor | — | — | Compare |
Explore Octopoda further
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Octopoda FAQ
How much does Octopoda cost?
Free is $0, Pro $19, Business $49 and Scale $99 per month; yearly billing saves 20%. source (opens in a new tab)
What counts as an agent?
Any distinct process calling Octopoda with its own identity; only concurrent registered agents count. source (opens in a new tab)
What happens if I hit my memory limit?
Writes keep working, you are notified, and you can prune, set TTLs or upgrade. source (opens in a new tab)
Can I self-host?
Yes, the MIT-licensed core runs local-first on SQLite; paid plans add cloud sync, dashboard and support. source (opens in a new tab)
Which frameworks are supported?
LangChain, CrewAI, AutoGen, OpenAI Assistants and Agents SDK, Anthropic, MCP and REST. source (opens in a new tab)
Sources and review methodology
Official sources and verification dates
- Octopoda - Persistent Memory for AI Agents homepage · checked Oct 1, 2026
- Pricing - Octopoda homepage · checked Oct 1, 2026
- https://octopodas.com/privacy policy · checked Oct 1, 2026
- https://octopodas.com/docs docs · checked Oct 1, 2026
Not verified: Enterprise pricing; Whether memory content is used for training.
How we documented and maintain this page
Every fact about Octopoda above comes from the 4 official pages listed here, last compared on Sep 29, 2026; we have not run Octopoda ourselves, so it has no editorial score. How we check and re-check pages.
Article updated Oct 10, 2026; prices checked Sep 29, 2026. Outbound links to vendors are plain links; we do not earn commissions. How we review · Report an error