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Rank #1 of 6 in AI Memory Layers

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Mem0

Open SourceYC S24

Mem0

mem0.ai ↗Try it →
PA Score47/100AGENT-READY77/100BUILT-IN AI30/100API33/100
MCP✓CLI✓API✓
★ 65.3k▲ 20.2k/yrnpm 92.4k/wkpypi 475.2k/wk★ +549npm/wk -39.7kpypi/wk +20.8k
ArenasAI Memory Layers#1/6

Access

Open app ↗API docs ↗CLI docs ↗MCP docs ↗

Install

pippip install mem0ai
npmnpm install mem0ai
clipip install mem0-cli

Compare head-to-head

Zep logovs ZepLetta logovs LettaSupermemory logovs SupermemoryCognee logovs CogneeAirweave logovs Airweave

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Showcase

Mem0 homepage screenshot
homepage · captured Sep 2026 · view live ↗
Mem0 docs screenshot
docs · captured Sep 2026 · view live ↗

Try itExperimental

See what an agent can do with Mem0 before you ever sign up. Pick a story: recorded sessions replay real probe-harness transcripts; the live MCP handshake runs real requests from our edge, right now — including, where the server allows it, one real read-only tool call (bring your own key for auth-gated servers); sandboxed self-drive sessions are designed and gated (docs/TRY-IT.md).

$uvx --from mem0-cli mem0 --helprecorded session — replayed, not live
recorded 2026-09-05 · exit 0 · captured verbatim by our probe harness, secrets redacted

Verified integrations

Connections to other tracked products — hover a chip for the verbatim evidence quote behind it.

Claude Code logoClaude CodeAI Coding AgentsCodex logoCodexAI Coding AgentsCrewAI logoCrewAIAgent Frameworks & SDKsCursor logoCursorAI Coding AgentsVercel logoVercelEdge & App Platforms

By theme — the product's score on each story themeBy theme

Agenticness — how well agents can access and operate the productAgenticnessevidence →

How well agents can access and operate the product

59.9/100

Automation depth — how much of the product can run unattendedAutomation depthevidence →

How much of the product can run unattended

21.6/100

Data lifecycle — stories about data lifecycle in this arenaData lifecycleevidence →

Stories about data lifecycle in this arena

58.7/100

Deployment self host — stories about deployment self host in this arenaDeployment self hostevidence →

Stories about deployment self host in this arena

60.0/100

Graph entity memory — stories about graph entity memory in this arenaGraph entity memoryevidence →

Stories about graph entity memory in this arena

48.0/100

Memory recall quality — stories about memory recall quality in this arenaMemory recall qualityevidence →

Stories about memory recall quality in this arena

49.7/100

Openness — open source, data portability, and self-hosting storiesOpennessevidence →

Open source, data portability, and self-hosting stories

46.8/100

Pricing plans — plan structure and value — what each tier costs and what it unlocksPricing plansevidence →

Plan structure and value — what each tier costs and what it unlocks

0.0/100

Privacy posture — data-handling and privacy storiesPrivacy postureevidence →

Data-handling and privacy stories

13.3/100

Retrieval performance — stories about retrieval performance in this arenaRetrieval performanceevidence →

Stories about retrieval performance in this arena

0.0/100

Sdk integrations — stories about sdk integrations in this arenaSdk integrationsevidence →

Stories about sdk integrations in this arena

43.4/100

Session context — stories about session context in this arenaSession contextevidence →

Stories about session context in this arena

19.5/100

Tenancy permissions — stories about tenancy permissions in this arenaTenancy permissionsevidence →

Stories about tenancy permissions in this arena

48.0/100

Story verdicts — every judged story with its evidenceStory verdicts

What’s free: 2 free · 0 paid · 0 enterprise · 38 not stated in evidence

?

Sorted by importance (agentic first) (high → low) · 57/57 stories · click a row’s chevron for the rationale and evidence

Drive the product through a documented public API G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3full9/10T

Connect an agent via an official MCP server G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3full8/10T

Plug MCP servers into this product so it can use their tools G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3n/a0/10

Delegate tasks to a built-in AI assistant inside the product G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness3n/auntestednone yet

Download a machine-readable API spec (OpenAPI or equivalent) G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full9/10T

Point an agent at llms.txt or agent-oriented docs G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full9/10T

Build against official SDKs G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full8/10T

Run the product headlessly / in CI for automation G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full8/10T

Subscribe to events via webhooks G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full8/10C

Use an official CLI G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full8/10T

Operate the product with natural-language commands G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial6/10C

Issue scoped/least-privilege API credentials for an agent G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial5/10C

Explore an interactive API reference with runnable examples G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial4/10T

Get AI-generated insights and suggestions from my data inside the product G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial4/10C

Rely on versioned APIs with a documented deprecation policy G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2noneuntestednone yet

Set up automations that run autonomously in the background G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2n/auntestednone yet

Test against a sandbox environment without touching production data G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness1noneuntestednone yet

Add memories from conversations and retrieve them later with semantic search, so context persists across sessions C

Core memory

developerMemory recall quality — stories about memory recall quality in this arenaMemory recall quality3full8/10X

My agent can manage its own memory mid-conversation — adding, searching, updating, and deleting memories through tools or API calls it invokes itself C

Agent memory

ai-native userMemory recall quality — stories about memory recall quality in this arenaMemory recall quality3full8/10T

Self-host the core product G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness3fullfree8/10C

Store memories as a knowledge graph of entities and relationships so multi-hop and entity-centric questions are answerable C

Knowledge graph

ml-engineerGraph entity memory — stories about graph entity memory in this arenaGraph entity memory3full8/10C

Scope memories per user, agent, or application so one tenant's memories never leak into another's retrieval C

Isolation

developerTenancy permissions — stories about tenancy permissions in this arenaTenancy permissions3full7/10C

Self-host the memory layer from open-source code (e.g. via Docker) on infrastructure I control C

Self host

platform-engineerDeployment self host — stories about deployment self host in this arenaDeployment self host3fullfree7/10C

Export all of my data in open formats and leave G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness3partial6/10C

Get summaries of past sessions or threads so an agent can pick up where the last conversation left off C

Context assembly

developerSession context — stories about session context in this arenaSession context3partial6/10T

Define rules that trigger actions automatically on events G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth3partial4/10C

Prevent my data from being used to train AI models G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture3noneuntestednone yet

Connect off-the-shelf assistants (Claude, ChatGPT, Cursor) to the same memory so every tool I use shares what it knows about me C

Agent memory

ai-native userSdk integrations — stories about sdk integrations in this arenaSdk integrations2full8/10T

Export memories in a machine-readable format so the memory store is portable and not a lock-in trap C

Portability

platform-engineerData lifecycle — stories about data lifecycle in this arenaData lifecycle2full7/10C

Make memories expire or decay — via TTL, expiration dates, or recency weighting — so stale facts stop surfacing C

Forgetting

developerData lifecycle — stories about data lifecycle in this arenaData lifecycle2full7/10C

The memory layer decides for itself what is worth remembering — extracting salient facts from raw conversation and consolidating them in the background C

Agent memory

ai-native userMemory recall quality — stories about memory recall quality in this arenaMemory recall quality2partial7/10X

Build against official SDKs in at least Python and TypeScript with equivalent memory APIs C

Sdks

developerSdk integrations — stories about sdk integrations in this arenaSdk integrations2partial6/10C

Control data retention and deletion G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2partial6/10C

Delete a user's memories on demand — single memory, per-entity, or full erasure — to satisfy privacy requirements C

Forgetting

platform-engineerData lifecycle — stories about data lifecycle in this arenaData lifecycle2partial6/10C

Do everything through the API that I can do in the UI G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness2partial6/10T

Drop the memory layer into agent frameworks like LangChain, LangGraph, CrewAI, or the Vercel AI SDK via documented first-party integrations C

Frameworks

developerSdk integrations — stories about sdk integrations in this arenaSdk integrations2partial6/10C

Steer retrieval with metadata filters, keyword/hybrid search modes, or reranking instead of accepting a single fixed similarity search C

Retrieval controls

developerMemory recall quality — stories about memory recall quality in this arenaMemory recall quality2partial6/10C

Rely on the memory layer to update, supersede, or merge memories when new information contradicts what was stored C

Core memory

developerMemory recall quality — stories about memory recall quality in this arenaMemory recall quality2partial5/10C

Choose where my data is stored (region/residency) G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2partial4/10C

Govern who and what can read or write memory with roles, policies, or access-control lists, and audit that access C

Governance

platform-engineerTenancy permissions — stories about tenancy permissions in this arenaTenancy permissions2partial4/10C

Read the product's source under an open license G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness2partial4/10C

Retrieve a token-budgeted, prompt-ready context block assembled from relevant memories in one call C

Context assembly

developerSession context — stories about session context in this arenaSession context2partial4/10C

Track when facts became valid or invalid (temporal reasoning) so the memory distinguishes current from outdated information C

Knowledge graph

ml-engineerGraph entity memory — stories about graph entity memory in this arenaGraph entity memory2partial4/10C

Perform bulk operations across many items at once G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth2partial3/10C

Ingest at scale with async or batch processing and check the status of background memory operations C

Scale

platform-engineerRetrieval performance — stories about retrieval performance in this arenaRetrieval performance2none0/10

Ingest documents, JSON, and business data into memory — not just chat transcripts C

Ingestion

developerSession context — stories about session context in this arenaSession context2none0/10

Opt out of telemetry and usage tracking G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2noneuntestednone yet

Schedule recurring jobs or workflows G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth2n/auntestednone yet

See documented retrieval-latency targets or measured numbers (e.g. p50/p95) backing the product's speed claims C

Latency

platform-engineerRetrieval performance — stories about retrieval performance in this arenaRetrieval performance2noneuntestednone yet

See published memory-quality benchmark results (e.g. LongMemEval, LoCoMo) backing the product's recall-accuracy claims C

Benchmarks

ml-engineerMemory recall quality — stories about memory recall quality in this arenaMemory recall quality2noneuntestednone yet

See published pricing with a free tier and per-unit rates so I can project memory costs before committing G

Pricing

platform-engineerPricing plans — plan structure and value — what each tier costs and what it unlocksPricing plans2noneuntestednone yet

Run the memory layer fully locally — embedded in-process or against local models — without any cloud dependency C

Self host

developerDeployment self host — stories about deployment self host in this arenaDeployment self host1partial5/10C

Share selected memory across multiple agents or users (team or group memory) while keeping private memory private C

Sharing

developerTenancy permissions — stories about tenancy permissions in this arenaTenancy permissions1partial5/10C

Customize the memory schema — entity types, edge types, or ontology — to match my domain C

Schema customization

ml-engineerGraph entity memory — stories about graph entity memory in this arenaGraph entity memory1none0/10

Store images, PDFs, or other files as memory inputs and recall information from them later C

Ingestion

developerSession context — stories about session context in this arenaSession context1none0/10

Wire memory into real-time voice pipelines (e.g. LiveKit, Pipecat, ElevenLabs) with documented integrations fast enough for live conversation C

Frameworks

developerSdk integrations — stories about sdk integrations in this arenaSdk integrations1none0/10

Version, review, and roll back my automations G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth1n/auntestednone yet

Opportunities — the stories that would move this product's scores, from its own judged verdictsOpportunitiestop 8 of 35 stories with headroom

What would move Mem0’s scores — derived from its own judged verdicts, biggest headroom first. Each line quotes what the judge found missing; shipping it (or evidencing it publicly) is the fix.

  1. Privacy posture — data-handling and privacy storiesPrevent my data from being used to train AI models

    nonemoves PA Scoreimpact 30

    No evidence anywhere in the pack addresses opting out of AI-model-training use of data, data-training policies, or contractual/privacy commitments about training; the docs focus entirely on memory storage/retrieval features.

  2. Agenticness — how well agents can access and operate the productRely on versioned APIs with a documented deprecation policy

    nonemoves API qualityimpact 30

    The evidence pack shows quickstart docs, an OpenAPI spec, and various feature docs, but nothing about API versioning scheme or a documented deprecation policy.

  3. Retrieval performance — stories about retrieval performance in this arenaIngest at scale with async or batch processing and check the status of background memory operations

    nonemoves PA Scoreimpact 20

    The evidence pack shows single add/search operations, CLI, webhooks, and quickstart flows, but nothing about async/batch ingestion APIs or a way to poll/check status of background memory operations.

  4. Session context — stories about session context in this arenaIngest documents, JSON, and business data into memory — not just chat transcripts

    nonemoves PA Scoreimpact 20

    All evidence describes Mem0's add/search API in terms of conversation messages (client.add(messages, user_id=...)) and fact extraction from chat turns; there is no mention of ingesting documents, PDFs, JSON payloads, or arbitrary business data as a memory source.

  5. Retrieval performance — stories about retrieval performance in this arenaSee documented retrieval-latency targets or measured numbers (e.g. p50/p95) backing the product's speed claims

    nonemoves PA Scoreimpact 20

    No evidence pack items mention latency numbers, p50/p95 metrics, or any documented performance/speed targets for retrieval; docs focus on features (search, graph memory, reranking) but never quantify speed.

  6. Privacy posture — data-handling and privacy storiesOpt out of telemetry and usage tracking

    nonemoves PA Scoreimpact 20

    No evidence in the pack discusses telemetry, usage tracking, or any opt-out/privacy configuration setting for Mem0; the docs cover memory features, self-hosting, MCP, and CLI but never mention telemetry controls.

  7. Memory recall quality — stories about memory recall quality in this arenaSee published memory-quality benchmark results (e.g. LongMemEval, LoCoMo) backing the product's recall-accuracy claims

    nonemoves PA Scoreimpact 20

    Missing: any benchmark citation, LongMemEval/LoCoMo results, accuracy/recall metrics, third-party evaluation.

  8. Pricing plans — plan structure and value — what each tier costs and what it unlocksSee published pricing with a free tier and per-unit rates so I can project memory costs before committing

    nonemoves PA Scoreimpact 20

    No evidence in the pack mentions pricing, free tier, or per-unit rates anywhere in the docs, community, or probes; all citations concern product features (memory ops, MCP, CLI, graph memory) rather than pricing plans.

Showing the top 8 of 35 — every none/partial verdict in the story verdicts table is headroom.

Think a verdict is wrong? Every verdicts-table row has a Flag link — see the methodology.

Coverage map — which docs area, API section, or community source covers which judged storiesCoverage map7 surfaces · 40 covered stories

Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.

Platform docs34 stories

Open source docs12 stories

docs.mem0.ai8 stories

OpenAPI spec7 stories

Core concepts docs7 stories

llms.txt2 stories

Hacker News2 stories

Probe proofs — replayable recordings from the probe harnessProbe proofs

Replayable recordings from our probe harness — see the Prove-It protocol to submit one.

$uvx --from mem0-cli mem0 --helpreproduced
$ uvx --from mem0-cli mem0 --help
⠋ Resolving dependencies...                                                     
⠙ Resolving dependencies...                                                     
⠋ Resolving dependencies...                                                     
⠙ Resolving dependencies...                                                     
⠙ mem0-cli==0.2.12                                                              
⠙ httpx==0.28.1                                                                 
⠙ rich==15.0.0                                                                  
⠙ typer==0.27.2                                                                 
⠙ anyio==4.15.0                                                                 
⠙ certifi==2026.7.22                                                            
⠙ httpcore==1.0.9                                                               
⠙ idna==3.19                                                                    
⠙ markdown-it-py==4.2.0                                                         
⠙ pygments==2.21.0                                                              
⠙ shellingham==1.5.4                                                            
⠙ annotated-doc==0.0.5                                                          
⠙ typing-extensions==4.16.0                                                     
⠙ typing-extensions==4.16.0                                                     
⠙ h11==0.16.0                                                                   
⠙ mdurl==0.1.2                                                                  
⠙                                                                               

 Usage: mem0 <command> [options]

 ◆ Mem0 CLI v0.2.12 · Python SDK

 The Memory Layer for AI Agents

╭─ Options ────────────────────────────────────────────────────────────────────╮
│ --version               Show version and exit.                               │
│ --json,--agent          Output as JSON for agent/programmatic use.           │
│ --help                  Show this message and exit.                          │
╰──────────────────────────────────────────────────────────────────────────────╯
╭─ Memory ─────────────────────────────────────────────────────────────────────╮
│ add         Add a memory from text, messages, file, or stdin.                │
│ search      Query your memory store — semantic, [redacted]word, or hybrid           │
│             retrieval.                                                       │
│ get         Get a specific memory by ID.                                     │
│ list        List memories with optional filters.                             │
│ update      Update a memory's text or metadata.                              │
│ delete      Delete a memory, all memories, or an entity.                     │
╰──────────────────────────────────────────────────────────────────────────────╯
╭─ Management ─────────────────────────────────────────────────────────────────╮
│ init        Interactive setup wizard for mem0 CLI.                           │
│ status      Check connectivity and authentication.                           │
│ version     Show version and exit.                                           │
│ import      Import memories from a JSON file.                                │
│ help        Show help. Use --json for machine-readable output (for LLM       │
│             agents).                                                         │
│ entity      Manage entities.                                                 │
│ event       Inspect background processing events.                            │
│ config      Manage mem0 configuration.                                       │
╰──────────────────────────────────────────────────────────────────────────────╯
╭─ Setup ──────────────────────────────────────────────────────────────────────╮
│ identify    Tag your active Agent Mode [redacted] with the AI agent that's using    │
│             it.                                                              │
│ whoami      Print your AGENTRUSH identifier (default_user_id).               │
│ agent-rush  AGENTRUSH game commands                                          │
╰──────────────────────────────────────────────────────────────────────────────╯
proves: Use an official CLIrecorded 2026-09-05
$curl -si -X POST https://mcp.mem0.ai/mcp/ -H 'Content-Type: application/json' -d '<jsonrpc initialize>'reproduced
$ curl -si -X POST https://mcp.mem0.ai/mcp/ -H 'Content-Type: application/json' -d '<jsonrpc initialize>'
HTTP/2 401

date: Sat, 05 Sep 2026 00:46:49 GMT

content-type: application/json

content-length: 74

server: cloudflare

www-authenticate: Bearer error="invalid_[redacted]", error_description="Authentication required", resource_metadata="https://mcp.mem0.ai/.well-known/oauth-protected-resource"

cf-cache-status: DYNAMIC

report-to: {"group":"cf-nel","max_age":604800,"endpoints":[{"url":"https://a.nel.cloudflare.com/report/v4?s=9Q2wXp7tke9ruAkYblh0c4wGH5MlwpBKA2H6lIK%2FXIR28ldX7AOvm1cYk9kVJQqN4k%2F50V9M1duc2OcT5O%2F6YJUKZnBkPiHqKflQXytCHXJ0iFm1M2kQKTjwGok6"}]}

nel: {"report_to":"cf-nel","success_fraction":0.0,"max_age":604800}

cf-ray: a361381978c136e8-SJC

{"error": "invalid_[redacted]", "error_description": "Authentication required"}
proves: Connect an agent via an official MCP serverrecorded 2026-09-05
$uv run --with mem0ai python3 -c 'import mem0; from mem0 import Memory; print("PA_PROBE_OK mem0ai", mem0.__version__)'reproduced
$ uv run --with mem0ai python3 -c 'import mem0; from mem0 import Memory; print("PA_PROBE_OK mem0ai", mem0.__version__)'
⠋ Resolving dependencies...                                                     
⠙ Resolving dependencies...                                                     
⠋ Resolving dependencies...                                                     
⠙ Resolving dependencies...                                                     
⠙ mem0ai==2.0.20                                                                
⠙ httpx==0.28.1                                                                 
⠙ openai==3.8.0                                                                 
⠙ posthog==7.47.0                                                               
⠙ protobuf==6.33.6                                                              
⠙ pydantic==2.13.5                                                              
⠙ pydantic-core==2.46.5                                                         
⠙ pytz==2026.3.post1                                                            
⠙ qdrant-client==1.19.0                                                         
⠙ httpx==0.28.1                                                                 
⠙ sqlalchemy==2.0.52                                                            
⠙ anyio==4.15.0                                                                 
⠙ certifi==2026.7.22                                                            
⠙ httpcore==1.0.9                                                               
⠙ idna==3.19                                                                    
⠙ httpx2==2.12.0                                                                
⠙ httpcore2==2.12.0                                                             
⠙ httpcore2==2.12.0                                                             
PA_PROBE_OK mem0ai 2.0.20
proves: Build against official SDKsproves: Self-host the memory layer from open-source code (e.g. via Docker) on infrastructure I controlrecorded 2026-09-05

Claims vs evidence — vendor claims reconciled against independent verdictsClaims vs evidence

6 of 18 testable claims verified · 0 contradicted → integrity 33/100

19 distinct capability claims found in Mem0’s own claimed-docs/GitHub materials, reconciled against our judge’s independent verdicts.

6

Verified

12

Unverified

0

Contradicted

22

Undersold

Verified (10)
Unverified (14)
Undersold (22)

Business model

open-sourcefree-tierusage-basedenterprise-custom

Apache-2.0 open-source core; managed Platform has a free tier, then usage-priced Starter/Pro plans by memory operations and retrievals, plus custom enterprise.

pricing ↗

Score trend

How this product’s scores have moved as evidence and verdicts are re-derived — a point per change, not per day.

PA Score48 (Sep 5 '26)47 (Sep 16 '26)
Agent-ready80 (Sep 5 '26)77 (Sep 16 '26)

Try Experimental

Run it in the microterminal →

Recorded agent sessions — and a live MCP handshake where the vendor ships one.

Flag

⚑ Flag a verdict

Think a verdict is wrong? Opens a prefilled GitHub issue — or use the ⚑ next to any verdict above.

Badge

Embed this product's score badge →

Hotlinked SVG — always shows the live current score.

For agents

This page as markdown/llms.txt

Data

Evidence (JSON)Verdicts (JSON)

Agent surface uptime MCP 100% · llms.txt 100% · openapi.json 100% (30d, checked every 6h since Sep 8 '26)