Mem0 vs Letta vs Supermemory
Side by side, from each listing’s own data. A row where every column says the same is shown once, dimmed.
 Mem0by Mem0Remove Mem0 from this comparison |  Lettaby LettaRemove Letta from this comparison |  Supermemoryby SupermemoryRemove Supermemory from this comparison | |
|---|---|---|---|
| Sets it apart | — |
| — |
| What it is | Persistent memory layer for AI agents and LLMs. Stores, searches, and retrieves user and session memories across frameworks. SDKs for Python and JS, managed or self-hosted. | Stateful agent framework with built-in memory. Agents persist context between sessions via structured memory blocks. Formerly MemGPT. Self-hosted or managed cloud. | Memory API for AI applications. Store and retrieve user memories, bookmarks, and knowledge with semantic search. One unified API for personal and enterprise memory. |
| Provider | Mem0 | Letta | Supermemory |
| Official vendor | Not an official listingSame for all | ||
| Verified | YesSame for all | ||
| Access | API, MCP | API, CLI | API, MCP |
| Auth | API KeySame for all | ||
| MCP server | In its setup guide | No MCP server | In its setup guide |
| CLI install | No CLI | In its docs | No CLI |
| API base URL | In its docsSame for all | ||
| Skills | Store and retrieve persistent user and session memories across agent frameworks, Semantic memory search to surface relevant context from past interactions, Share memory across multi-agent pipelines with fine-grained access controls, Learn and update user preferences automatically from conversation history, Monitor memory usage and search analytics via built-in dashboard | Persist agent state between sessions using structured in-context memory blocks, Dynamically edit and archive memory to maintain coherent long-horizon agent behavior, Orchestrate multi-agent pipelines where agents pass typed memory between each other, Execute tool calls with full persistence of tool outputs across sessions, Deploy self-hosted or cloud agents with consistent stateful behavior at scale | Ingest memories from any source via a unified memory ingestion pipeline, Semantic retrieval of relevant memories ranked by context similarity, Build shared knowledge bases accessible across teams and agent instances, Store multiple content formats including text, URLs, and structured data, Collaborate on shared memory spaces with role-based access control |
| Streaming | No | Yes | No |
| Push notifications | NoSame for all | ||
| Categories | Memory & StateSame for all | ||
| Tags | memory, rag, personalization, stateful-agents, python, javascript, open-source | memory, stateful-agents, memgpt, open-source, self-hosted, python, orchestration | memory, knowledge-base, rag, semantic-search, open-source |
| Listed since | Apr 8, 2026Same for all | ||
| Use it now | |||
Share this comparison
https://agentswitchboard.dev/compare?a=mem0&b=letta&c=supermemoryMore comparisons
- GitHub Copilot vs Cursor vs Codeium / Windsurf
Three AI coding assistants, each an official listing. Cursor and Windsurf are editors with multi-file edits and autonomous coding; GitHub Copilot is a pair programmer with an agent mode.
- LangGraph vs CrewAI vs AutoGen
Frameworks for multi-agent systems. LangGraph builds stateful graph workflows, CrewAI teams of agents that delegate, and AutoGen conversational and human-in-the-loop agents in Python and TypeScript.
- Mem0 vs Zep vs Letta
Three ways to give agents long-term memory. Mem0 and Zep are memory layers your agent calls; Letta is a stateful agent framework with memory built in. Mem0 also has an MCP server.
- Pinecone vs Qdrant vs Weaviate
Vector databases for RAG and semantic search. Pinecone is fully managed; Qdrant and Weaviate are open source. Beyond the API, Qdrant has a CLI and Weaviate an MCP server.
- Browserbase vs Browser Use vs Browserless
Browsers for AI agents. Browserbase and Browserless run headless browsers you drive with Playwright or Puppeteer; Browser Use is an open-source Python library that controls websites from natural-language instructions.
- E2B vs Daytona vs Vercel Sandbox
Sandboxes where agents run untrusted code, each with an API and a CLI. E2B runs Python, JS and shell; Daytona provisions dev environments with git; Vercel Sandbox uses Firecracker microVMs.
- Firecrawl vs Crawl4AI vs Jina Reader
All three turn web pages into clean Markdown for LLMs. Firecrawl and Jina Reader take an API key; Crawl4AI needs no auth and adds deep crawling and browser session control.
- Figma MCP Server vs Figma Context MCP vs Talk to Figma MCP
MCP servers that bring Figma designs to coding agents. Figma's own server can also write back to the canvas; Framelink's reads layout and styles; Grab's edits nodes through a Figma plugin.
- Ollama vs LM Studio vs vLLM
Run open models on your own hardware behind an OpenAI-compatible API, with no auth. Ollama and LM Studio run models locally; vLLM is a high-throughput inference server.
- Asana MCP vs ClickUp MCP vs monday.com MCP
Official project-management MCP servers, all hosted with OAuth sign-in. monday.com also has a local npm package and its GraphQL API; ClickUp's is in public beta with no deletion tools.
- Groq vs Cerebras Inference
Fast inference APIs for open models, both OpenAI-compatible with streaming. Groq runs on its own LPU hardware; Cerebras serves models such as Qwen and GPT OSS on wafer-scale chips.
- Deepgram vs AssemblyAI
Speech-to-text APIs with real-time streaming. Deepgram adds text-to-speech for voice agents and a CLI; AssemblyAI adds audio intelligence such as summarization and redaction.
- Neon MCP vs PlanetScale MCP
MCP servers for managed SQL databases with branching. Neon's manages serverless Postgres with an API key; PlanetScale's signs in with OAuth and covers Vitess and Postgres.
