MemMachine: Pricing, Features & Best Use Cases

Our take: Choose MemMachine if you are a developer who wants an open-source memory layer that keeps user facts and conversation context across sessions, agents and different language models.

Main limitation: It is a developer component reached through REST API, Python SDK or MCP server, not an end-user app, and the Pro price mapping to the billing toggle is unclear.

By the AI Tool Atlas editors. Based on the vendor's official documentation; we have not tested this product hands-on. What “documented overview” means

Who should use MemMachine

Choose MemMachine if you are a developer who wants an open-source memory layer that keeps user facts and conversation context across sessions, agents and different language models. Based on the vendor's documentation, not on a hands-on test.

Best for: Agent developers

Also a good fit for

Teams building production AI agents
Organizations needing self-hosted memory

Consider another tool if primarily for developers, not end users

Or if

Self-hosting requires your own infrastructure
Pro plan is billed per project at $79/mo

MemMachine pricing and usage limits

Prices checked Oct 2, 2026 on the official US pricing page. Official pricing ↗ Prices and limits change often.

The official MemMachine pricing page as we saw it. memmachine.ai, captured Oct 2, 2026

Free access and trial conditions

Open Source edition is $0 forever and self-hosted; the site also advertises a free sandbox.

Pro lists a Start for Free button; trial length is not stated.

Paid plans: what changes as you upgrade

Open Source api

Free source (opens in a new tab)

For: Developers building locally

Includes

All memory types
Core integrations

2 more

Self-hosted deployment
Community support

API included

Pro api

See official pricing source (opens in a new tab)

Monthly or yearly toggle

Page shows $79/mo with a Monthly/Yearly (Save 15%) toggle; the page text does not say which state the figure belongs to, so price is left null.

For: Teams building production agents

Limits

Billed per project

Includes

Managed cloud hosting
Higher rate limits

2 more

Premium integrations
Email and chat support

API included

Enterprise api

Custom pricing source (opens in a new tab)

For: Organizations needing compliance control

Includes

On-premise or VPC deployment
Custom SLAs and 24/7 support

2 more

SSO and advanced security
Dedicated engineer

API included

Usage caps, credits and extra costs

Pro is billed per project.

What is MemMachine, and how does it work?

MemMachine is an open-source memory layer for AI agents. It lets applications learn, store and recall data and preferences from past sessions, and its memory persists across sessions, agents and language models. It is aimed at agent developers and organizations. It can be self-hosted for free or used as a managed cloud service on a paid plan.

MemMachine's official site: how the product presents itself. memmachine.ai, captured Oct 2, 2026

What you provide and what you get back

What you give MemMachine and what comes back, from its documentation

You provide

Agent conversation messages
User facts and preferences
API calls from a REST client, Python SDK or MCP server

You get back

Recalled episodic conversation context
Stored profile memory about each user
Context passed back into the agent prompt

Where you can use it

Platforms: API
Access methods: REST API, Python SDK, MCP server
Memory types: Short-term, long-term, personalization; episodic and profile storage
Storage: Graph database for episodic, SQL database for profile
Hosting: Self-hosted (free), managed cloud (Pro), on-premise or VPC (Enterprise)
Support: Community; email and chat on Pro; 24/7 on Enterprise

Where MemMachine is most useful

Scenarios are worked out by our editors from the documentation; the actual result depends on your input and plan.

Adding persistent memory to chatbots

Who: Developers building chatbots
You provide: Conversation history sent to the memory API
Expected result: Chatbot that recalls earlier sessions
Plan needed: Open Source or Pro
Limitation: Requires integration work in the agent code source (opens in a new tab)

Personalizing AI assistants with user profiles

Who: Teams building personalized assistants
You provide: User preferences and history
Expected result: Profile memory that adjusts answers to the user
Plan needed: Open Source or Pro
Limitation: Profile memory is stored in an SQL database that must be run when self-hosting source (opens in a new tab)

Sharing memory across several agents and models

Who: Multi-agent and multi-model builders
You provide: Memory shared from several agents and models
Expected result: One consistent memory across vendors
Plan needed: Open Source, Pro or Enterprise
Limitation: Quality depends on how each agent writes to memory source (opens in a new tab)

Key features and their practical limits

Feature overview on the official site. memmachine.ai, captured Oct 2, 2026

Short-term, long-term and personalization memory types

Stores conversational context as episodic memory and long-term user facts as profile memory, in addition to short-term memory. Lets agents recall earlier sessions and personal facts.

Access: All plans list all memory typesLimit: Episodic memory runs on a graph database that must be set up when self-hosting. source (opens in a new tab)

Model-agnostic memory across multiple LLMs

Keeps memory outside any single model vendor so several LLMs can read the same memory. Avoids lock-in to one vendor memory service.

Access: All plansLimit: Each model integration needs to be wired up by the developer. source (opens in a new tab)

Open-source self-hosted deployment

Offers the open-source edition for self-hosting on your own infrastructure with community support. Keeps data on infrastructure you control.

Access: Open Source plan, $0 foreverLimit: Support is community only through Discord and GitHub. source (opens in a new tab)

Managed cloud hosting on the Pro plan

Runs MemMachine as a managed cloud service billed per project, with higher rate limits and premium integrations. Removes hosting work for production agents.

Access: Pro planLimit: Rate limit numbers are not published. source (opens in a new tab)

Pros, cons and deal-breakers

Reasons to choose MemMachine

Open-source edition is free forever and self-hosted Lets teams run it at no license cost. documented source (opens in a new tab)
Works with multiple AI models, not tied to one vendor Lets teams keep several LLM vendors without losing memory. documented source (opens in a new tab)
Public documentation with many framework integration guides Makes it easier for developers to find setup steps, though the docs URL returned 404 when fetched. documented source (opens in a new tab)

Check before paying for MemMachine

Primarily for developers, not end users Product managers and non-coders cannot use it directly. documented source (opens in a new tab)
Self-hosting requires your own infrastructure Teams need to run databases and hosting themselves for the free edition. documented source (opens in a new tab)
Pro plan is billed per project at $79/mo Cost is per project, so teams with several projects pay for each. documented source (opens in a new tab)
Enterprise pricing is custom and requires contacting sales Large organizations must go through sales for on-premise or VPC. documented source (opens in a new tab)

How to use MemMachine for adding persistent memory to an AI agent

Set up MemMachine

Open the MemMachine GitHub repository from the pricing page for the self-hosted edition.
Deploy the memory core on your own infrastructure with its graph and SQL databases.
Pick an access method: REST API, Python SDK or MCP server.
Point your agent at the MemMachine endpoint.

Example: adding persistent memory to an AI agent

Send a user message from your chatbot to the memory API.
Store a stated preference such as a preferred appointment time as profile memory.
Start a new session and query memory for that user.
Insert the recalled facts into the agent prompt.

Review and export the result

Ask the agent in a new session about the stored preference and confirm it answers correctly.
Inspect the stored profile entry for the expected user.

MemMachine API

Plan comparison on the official pricing page. memmachine.ai, captured Oct 2, 2026

API access and separate billing

MemMachine has no public API in its official documentation. RESTful API, Python SDK and MCP server are named on the homepage; docs URL returned 404 when fetched. 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

Memory is stored in a graph database (episodic) and an SQL database (profile).

Commercial use and plan restrictions

Open source edition can be deployed in a private cloud or on-premises for full control over data; Enterprise adds on-premise or VPC deployment.

Controls for business users

SSO and advanced security on Enterprise
On-premise or VPC on Enterprise

MemMachine alternatives by need

"Better suited" is based on documented features and pricing, not on a head-to-head test.

n8n: better suited to

Zapier: better suited to

Alternatives
Alternative	When to choose it	Pricing	Limitation
n8n		—	—
Zapier		—	—

Explore MemMachine further

MemMachine pricing, plan by planEvery plan with USD prices, limits and what is free.Best MemMachine alternativesTools for the same job, by need and starting price.Best AI coding toolsOur picks in this category, compared by price and free tiers.

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MemMachine FAQ

Is MemMachine meant for developers or end users?

MemMachine says it is primarily designed for agent developers and organizations building AI applications. source (opens in a new tab)

How much does MemMachine Pro cost?

The pricing page shows Pro at $79 per month billed per project, with a Monthly/Yearly toggle (yearly saves 15%); the page does not state which toggle state the $79 belongs to. source (opens in a new tab)

Who develops MemMachine?

The project was incubated by MemVerge and is now community-driven, with MemVerge continuing to assign engineers. source (opens in a new tab)

What are the MemMachine memory types?

It offers short-term, long-term and personalization memory; episodic memory sits in a graph database and profile memory in an SQL database. source (opens in a new tab)

Where does MemMachine support come from on the open-source edition?

Community channels: a Discord server and GitHub issues. source (opens in a new tab)

Sources and review methodology

Official sources and verification dates

MemMachine homepage · checked Oct 2, 2026
Pricing Plans | MemMachine homepage · checked Oct 2, 2026
Welcome - MemMachine Documentation homepage · checked Oct 2, 2026

Not verified: Pro price mapping to the Monthly/Yearly toggle; Free trial duration; Privacy policy (404); Documentation page (404); Rate limits; Data retention.

How we documented and maintain this page

Every fact about MemMachine above comes from the 3 official pages listed here, last compared on Oct 2, 2026; we have not run MemMachine ourselves, so it has no editorial score. How we check and re-check pages.

Article updated Oct 2, 2026; prices checked Oct 2, 2026. Outbound links to vendors are plain links; we do not earn commissions. How we review · Report an error