Letta (formerly MemGPT) Review 2026

Name: Letta (formerly MemGPT)
Brand: Letta (formerly MemGPT)
Availability: InStock

Honest pros, cons, and verdict on this ai memory & search tool

✅ Purpose-built for persistent agent memory, making it a stronger fit than stateless chat tools for assistants that need to remember users, preferences, and prior work across sessions.

Starting Price

Free ($0/month)

Free Tier

Yes

What is Letta (formerly MemGPT)?

AI memory platform for building stateful agents that can preserve selected context across sessions, manage long conversations, and support applications that need durable agent memory.

Letta, formerly MemGPT, is a developer-focused platform for building stateful AI agents whose memory can persist beyond a single prompt, giving teams a practical way to create assistants that remember selected user, task, document, and workflow context across sessions while still exposing programmable controls through APIs, SDKs, hosted services, and self-hosted deployment patterns. Its core value is not simply longer chat history; it is an architecture for deciding which facts should live in active context, which should move to archival memory, and how an agent should retrieve or update that information during future work.

The platform is best understood as memory infrastructure for agent applications. Letta's public API documentation identifies a REST API with versioned v1 endpoints for agents, messages, tools, blocks, folders, files, archives, passages, models, MCP servers, runs, steps, feedback, conversations, and access tokens. That breadth matters because persistent memory becomes useful only when it is connected to the rest of the agent lifecycle: creating agents, attaching memory blocks, sending messages, running tools, searching archival memory, importing or exporting agents, and managing files or folders. The API reference also lists official client libraries for TypeScript and Python, with the TypeScript package shown as @letta-ai/letta-client and the Python package shown as letta-client, giving engineering teams two common implementation paths.

Key Features

✓Persistent memory across sessions

✓Virtual context management

✓Self-editing memory agents

✓Document analysis beyond context limits

✓Multi-session conversation tracking

Pricing Breakdown

Free

$0/month

per month

✓5,000 monthly credits
✓API access
✓Visual agent editing in the ADE
✓2 agent templates
✓1 GB of storage

API Plan

$20/month plus usage-based charges

per month

✓Unlimited agents
✓$0.10 per active agent per month
✓$0.00015 per second for server-side tool execution
✓Pay-as-you-go LLM usage
✓API access for production agent development

Enterprise

Custom pricing

per month

✓SAML/OIDC SSO
✓RBAC
✓Dedicated support
✓Increased quotas
✓Private model deployment options

Pros & Cons

✅Pros

•Purpose-built for persistent agent memory, making it a stronger fit than stateless chat tools for assistants that need to remember users, preferences, and prior work across sessions.
•Supports both cloud-hosted and self-hosted deployment according to the existing directory record, giving technical teams a path for managed usage or more direct infrastructure control.
•Model-agnostic positioning allows teams to design around an agent memory layer instead of tying all context and behavior to a single LLM provider.
•Its virtual context approach addresses a concrete limitation of LLM applications: important information can outlive the immediate context window instead of being lost between sessions.
•The existing listing identifies 5 core feature areas, including persistent memory, virtual context, self-editing agents, document analysis beyond context limits, and multi-session conversation tracking.
•Compared to broader agent frameworks in our directory, Letta has a clearer focus on long-running, stateful agents rather than general workflow orchestration.

❌Cons

•The provided scraped website content did not expose complete current customer counts, founding year, or integration counts, so buyers should verify commercial details before procurement.
•Persistent memory adds design and governance complexity because teams must decide what agents should store, retrieve, update, or forget over time.
•Usage-based charges on the API Plan, including $0.10 per active agent per month and $0.00015 per second for server-side tool execution, can make costs harder to forecast for high-volume applications.
•Self-hosted deployment can require engineering resources for installation, model provider configuration, monitoring, upgrades, and data management.
•Letta is more specialized than broad frameworks like LangChain or Semantic Kernel, so teams that mainly need general tool orchestration may find its memory-first focus narrower.

Who Should Use Letta (formerly MemGPT)?

✓Building a customer support assistant that remembers previous support tickets, product preferences, and unresolved issues across multiple conversations.
✓Creating a developer coding assistant that retains context from earlier debugging sessions, architecture discussions, and repository-specific conventions.
✓Deploying an internal knowledge agent that gradually accumulates institutional context about company policies, team workflows, and recurring operational questions.
✓Powering a long-running research assistant that tracks hypotheses, source notes, document summaries, and user feedback across weeks or months of work.
✓Adding memory to a personalized AI companion or coaching application where user goals, preferences, and prior conversations materially affect future responses.
✓Testing memory-first agent architectures before committing to a broader production stack that may also include orchestration, retrieval, and monitoring tools.

Who Should Skip Letta (formerly MemGPT)?

×You're concerned about the provided scraped website content did not expose complete current customer counts, founding year, or integration counts, so buyers should verify commercial details before procurement.
×You need something simple and easy to use
×You're on a tight budget

Alternatives to Consider

LangChain

The industry-standard framework for building production-ready LLM applications with comprehensive tool integration, agent orchestration, and enterprise observability through LangSmith.

Starting at Free

Learn more →

Microsoft AutoGen

Microsoft's open-source framework for building multi-agent AI systems with asynchronous, event-driven architecture.

Starting at Free

Learn more →

CrewAI

Open-source Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a 'crew' to complete complex tasks.

Starting at Free

Learn more →

Our Verdict

✅

Letta (formerly MemGPT) is a solid choice

Letta (formerly MemGPT) delivers on its promises as a ai memory & search tool. While it has some limitations, the benefits outweigh the drawbacks for most users in its target market.

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Frequently Asked Questions

What is Letta (formerly MemGPT)?

AI memory platform for building stateful agents that can preserve selected context across sessions, manage long conversations, and support applications that need durable agent memory.

Is Letta (formerly MemGPT) good?

Yes, Letta (formerly MemGPT) is good for ai memory & search work. Users particularly appreciate purpose-built for persistent agent memory, making it a stronger fit than stateless chat tools for assistants that need to remember users, preferences, and prior work across sessions.. However, keep in mind the provided scraped website content did not expose complete current customer counts, founding year, or integration counts, so buyers should verify commercial details before procurement..

Is Letta (formerly MemGPT) free?

Yes, Letta (formerly MemGPT) offers a free tier. However, paid plans start at Free ($0/month) and unlock additional functionality for professional users.

Who should use Letta (formerly MemGPT)?

Letta (formerly MemGPT) is best for Building a customer support assistant that remembers previous support tickets, product preferences, and unresolved issues across multiple conversations. and Creating a developer coding assistant that retains context from earlier debugging sessions, architecture discussions, and repository-specific conventions.. It's particularly useful for ai memory & search professionals who need persistent memory across sessions.

What are the best Letta (formerly MemGPT) alternatives?

Popular Letta (formerly MemGPT) alternatives include LangChain, Microsoft AutoGen, CrewAI. Each has different strengths, so compare features and pricing to find the best fit.

More about Letta (formerly MemGPT)

Pricing Alternatives Free vs Paid Pros & Cons Worth It?Tutorial

📖 Letta (formerly MemGPT) Overview 💰 Letta (formerly MemGPT) Pricing 🆚 Free vs Paid 🤔 Is it Worth It?

Last verified March 2026

What is Letta (formerly MemGPT)?

AI memory platform for building stateful agents that can preserve selected context across sessions, manage long conversations, and support applications that need durable agent memory.

Pricing Breakdown

Free

$0/month

per month

✓5,000 monthly credits
✓API access
✓Visual agent editing in the ADE
✓2 agent templates
✓1 GB of storage

API Plan

$20/month plus usage-based charges

per month

✓Unlimited agents
✓$0.10 per active agent per month
✓$0.00015 per second for server-side tool execution
✓Pay-as-you-go LLM usage
✓API access for production agent development

Enterprise

Custom pricing

per month

✓SAML/OIDC SSO
✓RBAC
✓Dedicated support
✓Increased quotas
✓Private model deployment options

Pros & Cons

✅Pros

•Purpose-built for persistent agent memory, making it a stronger fit than stateless chat tools for assistants that need to remember users, preferences, and prior work across sessions.
•Supports both cloud-hosted and self-hosted deployment according to the existing directory record, giving technical teams a path for managed usage or more direct infrastructure control.
•Model-agnostic positioning allows teams to design around an agent memory layer instead of tying all context and behavior to a single LLM provider.
•Its virtual context approach addresses a concrete limitation of LLM applications: important information can outlive the immediate context window instead of being lost between sessions.
•The existing listing identifies 5 core feature areas, including persistent memory, virtual context, self-editing agents, document analysis beyond context limits, and multi-session conversation tracking.
•Compared to broader agent frameworks in our directory, Letta has a clearer focus on long-running, stateful agents rather than general workflow orchestration.

❌Cons

•The provided scraped website content did not expose complete current customer counts, founding year, or integration counts, so buyers should verify commercial details before procurement.
•Persistent memory adds design and governance complexity because teams must decide what agents should store, retrieve, update, or forget over time.
•Usage-based charges on the API Plan, including $0.10 per active agent per month and $0.00015 per second for server-side tool execution, can make costs harder to forecast for high-volume applications.
•Self-hosted deployment can require engineering resources for installation, model provider configuration, monitoring, upgrades, and data management.
•Letta is more specialized than broad frameworks like LangChain or Semantic Kernel, so teams that mainly need general tool orchestration may find its memory-first focus narrower.

Who Should Use Letta (formerly MemGPT)?

✓Building a customer support assistant that remembers previous support tickets, product preferences, and unresolved issues across multiple conversations.
✓Creating a developer coding assistant that retains context from earlier debugging sessions, architecture discussions, and repository-specific conventions.
✓Deploying an internal knowledge agent that gradually accumulates institutional context about company policies, team workflows, and recurring operational questions.
✓Powering a long-running research assistant that tracks hypotheses, source notes, document summaries, and user feedback across weeks or months of work.
✓Adding memory to a personalized AI companion or coaching application where user goals, preferences, and prior conversations materially affect future responses.
✓Testing memory-first agent architectures before committing to a broader production stack that may also include orchestration, retrieval, and monitoring tools.

Alternatives to Consider

LangChain

The industry-standard framework for building production-ready LLM applications with comprehensive tool integration, agent orchestration, and enterprise observability through LangSmith.

Starting at Free

Learn more →

Microsoft AutoGen

Microsoft's open-source framework for building multi-agent AI systems with asynchronous, event-driven architecture.

Starting at Free

Learn more →

CrewAI

Open-source Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a 'crew' to complete complex tasks.

Starting at Free

Learn more →

Frequently Asked Questions

What is Letta (formerly MemGPT)?

AI memory platform for building stateful agents that can preserve selected context across sessions, manage long conversations, and support applications that need durable agent memory.

Is Letta (formerly MemGPT) good?

Is Letta (formerly MemGPT) free?

Yes, Letta (formerly MemGPT) offers a free tier. However, paid plans start at Free ($0/month) and unlock additional functionality for professional users.

Who should use Letta (formerly MemGPT)?

What are the best Letta (formerly MemGPT) alternatives?

Popular Letta (formerly MemGPT) alternatives include LangChain, Microsoft AutoGen, CrewAI. Each has different strengths, so compare features and pricing to find the best fit.