Does Mem0 support MCP and tool calling?

Full under the Agentic Index verification standard. Mem0 publishes public evidence of Model Context Protocol (MCP) support, tool calling, and API or SDK extensibility for connecting agents to external tools. Evidence basis: The Platform exposes a REST API for adding, searching, updating, exporting and deleting memories, with Python and TypeScript SDK clients, a CLI and an MCP server, and the open-source edition ships a self-hosted REST API server. Mem0, docs.m. Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

Does Mem0 have SOC 2, SSO and role based access control?

Full under the Agentic Index verification standard. Mem0 publishes public evidence of enterprise security and identity controls, covering a compliance posture such as SOC 2 or ISO 27001, single sign on (SSO or SAML), and role based access control (RBAC). Evidence basis: Enterprise adds SSO and audit logs, memories are partitioned per user, agent and app for tenant separation, and the self-hosted server runs with its own authentication and API keys; the site footer carries a SOC 2 Type I badge and links a T. Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

Can Mem0 be self hosted or run in a private VPC?

Full under the Agentic Index verification standard. Mem0 publishes public evidence of self hosted or private VPC deployment, along with data residency options for controlling where agent data is processed and stored. Evidence basis: Customers can run Mem0 as the managed Platform, as open-source software self-hosted with the bundled REST server and dashboard on the customer's own vector store and Postgres, or as an on-premises deployment on the Enterprise plan. Mem0, me. Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

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Mem0

Q: What are the best alternatives to Mem0?

Based on documented capability coverage across the Agentic Index 14 point taxonomy, the closest alternatives to Mem0 among agent infrastructure platforms are Zep, Cognee, Hyperspell, Deepgram. Each is graded on the same public evidence, and no vendor pays for placement.

Also known as: mem0, mem-zero, mem0ai

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Agent infrastructureindependentVerified 2026-09-21

Entry priceFrom $19/mo · free tier (10k add, 1k retrieval/mo) + open sourceFull pricing detail

Open source memory layer for AI agents: extracts facts from interactions and returns relevant memories on later calls, scoped per user, agent, app and run, via API, SDKs, CLI and MCP.

Mem0 is a memory layer for AI agents and assistants. Language models are stateless, so every call starts from a blank slate; after each interaction Mem0 extracts the durable facts, such as a user's preferences, decisions and prior context, stores them, and on the next call returns only the relevant ones to add to the prompt, so agents remember across sessions without replaying whole transcripts. It is open source under Apache 2.0 and also sold as the managed Mem0 Platform.

Memories are scoped by user, agent, application and run, so one agent can keep separate context per customer and short-lived sessions can expire on their own; memories can be updated, given an expiry date or deleted per user, and retrieval combines semantic search, keyword matching and entity linking, with optional decay of stale memories and a consolidation feature called Dream on higher plans. Mem0 works with LangGraph, CrewAI, the OpenAI Agents SDK, Google ADK, Mastra, Claude Code, Cursor and many other frameworks and tools, and developers reach it through a REST API, Python and TypeScript SDKs, a CLI and an MCP server; an agent can mint its own API key from the command line.

The open-source edition runs on the customer's own infrastructure with their choice of LLM, embedder and vector store, and Enterprise adds on-premises deployment, audit logs and SSO. The site shows a SOC 2 Type I badge and HIPAA and GDPR readiness. The Platform has a free Hobby tier with 10,000 add and 1,000 retrieval requests a month, Starter at $19 a month, Pro at $249 a month with graph memory and Dream, and a custom Enterprise tier, with usage-based pricing available.

Vendor details

Canonical URL

https://mem0.ai

Subcategory

Agent memory

Funding status

Founded by Taranjeet Singh (CEO) and Deshraj Yadav (CTO), the team behind Embedchain, with around $24M raised. The open source project has roughly 48,000 GitHub stars. Independent.

Company status

independent

Use cases & customers

Primary use cases

agent memorypersonalizationcross session contexttoken cost reductionconversational recall

Target customers

developersenterprise

Deployment options

SaaSself-hostedon-prem

Integrations

Framework agnostic with a simple add and search API and SDKs, integrating with LangChain, LangGraph, CrewAI, and AWS Strands Agents, and exposable as an MCP server. Self hosting orchestrates a vector store like Qdrant plus Postgres, and managed backends include Amazon ElastiCache for Valkey and Neptune Analytics for graph memory.

In practice

Your support bot asks returning users the same questions every session. You add Mem0 keyed by user, so it stores each user's preferences and recalls them next time without replaying the whole transcript.

Your token bill is high because you stuff full chat history into every prompt. Mem0 extracts and retrieves only the relevant memories, cutting context size and cost while keeping the agent's recall.

You need agent memory that stays in your environment for compliance. You self host Mem0 alongside your own Qdrant and Postgres, or deploy it air gapped, keeping every stored memory inside your boundary.

Sources & related URLs

Related / legacy domains

https://docs.mem0.ai https://github.com/mem0ai/mem0

Research sources

https://mem0.ai https://mem0.ai/pricing https://github.com/mem0ai/mem0

Agentic Index coverage score

6.0 / 14 capabilities · 43%

Integrations & Tool Calling	Partial
Mem0 ships native integrations that wire memory into more than twenty agent frameworks and coding tools, among them LangGraph, CrewAI, the OpenAI Agents SDK, Google ADK, Mastra, Claude Code and Cursor, plus n8n and Zapier, and webhooks notify other systems when memories change. These wire Mem0 into agents, but it does not give agents authenticated read and write actions in outside systems. SourceMem0, docs.mem0.ai integrations and platform/features/webhooks (indexed in llms.txt)read 2026-09-21
Workflow Orchestration	Not documented
Provides a memory layer that agent frameworks call, but does not orchestrate agent workflows, sequencing, or branching itself. Sourcemem0.airead 2026-09-21
Knowledge Grounding & RAG	Not documented
Retrieval runs over the memory store Mem0 extracts from interactions; no separate document index or knowledge base over the customer's content, alongside the memory layer, is documented in its documentation index. SourceMem0, docs.mem0.ai llms.txt and platform/features/entity-scoped-memoryread 2026-09-21
Human Oversight & Guardrails	Not documented
Offers no human review, approval workflow, or content guardrails; it stores and retrieves memories. Sourcemem0.airead 2026-09-21
Security, Identity & Governance	Full
Enterprise adds SSO and audit logs, memories are partitioned per user, agent and app for tenant separation, and the self-hosted server runs with its own authentication and API keys; the site footer carries a SOC 2 Type I badge and links a Trust Center. SourceMem0, mem0.ai/pricing and docs.mem0.ai platform/features/entity-scoped-memoryread 2026-09-21
Observability & Auditability	Partial
Pro adds advanced analytics and Enterprise adds audit logs of memory reads and writes, and memories can be inspected by user, agent, app and run in the dashboard, so the agent's memory activity is on the record. Mem0 sees only the memory calls made to it, not the steps and tool calls in the rest of the agent's run. SourceMem0, mem0.ai/pricing and docs.mem0.ai platform/features/entity-scoped-memoryread 2026-09-21
Memory & State Persistence	Full
Mem0 extracts facts from each interaction into a memory store the agent searches as context on later calls, scoped by user_id, agent_id, app_id and run_id so each customer, agent or session keeps its own memory; run-scoped memories expire independently, memories can be updated, given an expiry date or deleted for one user without touching others, and decay and consolidation keep stale facts from surfacing. SourceMem0, docs.mem0.ai platform/features/entity-scoped-memory and llms.txtread 2026-09-21
Deployment & Data Residency	Full
Customers can run Mem0 as the managed Platform, as open-source software self-hosted with the bundled REST server and dashboard on the customer's own vector store and Postgres, or as an on-premises deployment on the Enterprise plan. SourceMem0, mem0.ai/pricing and docs.mem0.ai open-source/setup (indexed in llms.txt)read 2026-09-21
Prebuilt Agents, Templates & Packs	Not documented
Provides example integrations but no prebuilt agents, templates, or installable packs. Sourcemem0.airead 2026-09-21
Triggers & Channel Coverage	Not documented
Exposed as an API that agents call; provides no triggers, scheduling, or conversational channel coverage of its own. Sourcemem0.airead 2026-09-21
Model Flexibility & Routing	Full
The open-source Memory class is configured with the customer's choice of LLM, embedder, vector store and reranker, and Mem0 works with AWS Bedrock and OpenAI-compatible endpoints, so the customer controls which model extracts and ranks memories. Mem0 itself is not a model routing gateway. SourceMem0, docs.mem0.ai open-source/configuration (indexed in llms.txt) and github.com/mem0ai/mem0read 2026-09-21
APIs, SDKs & MCP Extensibility	Full
The Platform exposes a REST API for adding, searching, updating, exporting and deleting memories, with Python and TypeScript SDK clients, a CLI and an MCP server, and the open-source edition ships a self-hosted REST API server. SourceMem0, docs.mem0.ai platform/features/entity-scoped-memory and llms.txtread 2026-09-21
Testing, Debugging & Optimization	Not documented
Mem0 publishes an evaluation framework and benchmark results for its own memory algorithm, which measure the vendor's product rather than the customer's agent; no scored test cases, harness or quality gate for evaluating a customer's agent is documented. SourceMem0, docs.mem0.ai core-concepts/memory-evaluation (indexed in llms.txt) and github.com/mem0ai/mem0read 2026-09-21
Browser & Computer Use	Not documented
Not applicable. Mem0 is a memory layer and does not provide browser automation or computer use; its browser extension only captures memories. Sourcemem0.airead 2026-09-21

The Agentic Index coverage score grades every vendor Full, Partial or Not documented against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded

Recent platform changes

2026-07-18·Memory / statePartially Verified

Mem0 introduced a multi-signal retrieval redesign in its open-source memory algorithm. The update replaces external graph store support with built-in entity linking, running semantic similarity, BM25 keyword matching, and entity matching in parallel before fusing them into a single result score.

Bears on: Memory / state

View source

View all 1 change for Mem0 →Tracked since Jul 2026 · Verified from public vendor sources

Pricing

From $19/mo · free tier (10k add, 1k retrieval/mo) + open source

Subscription tiers metered by memory add and retrieval requests per month and number of projects; usage based pricing also available

Free tier

Included quota

Hobby free (10,000 add, 1,000 retrieval requests/mo, 1 project). Starter $19/mo (50,000 add, 5,000 retrieval, 1 project). Pro $249/mo (500,000 add, 50,000 retrieval, unlimited projects, private Slack, advanced analytics, graph memory entity linking, Dream consolidation). Enterprise custom (unlimited, SLA, on-prem deployment, audit logs, custom integrations, SSO).

What is public

Self-serve tier pricing (Hobby free, Starter $19, Pro $249) with add, retrieval and project limits is public; Enterprise is custom and usage-based pricing is available.

Billing mechanics

Subscription tiers metered by monthly add (write) and retrieval (read) requests and project count. Each add request triggers an LLM call to extract memories. Open source self hosting has no request metering; enterprise adds on-prem and SLA under custom pricing.

Cost watchouts

Each memory add triggers an LLM call you pay for, so high turn chat workloads inflate both request counts and underlying model cost; self hosting moves spend to your own vector store and Postgres infrastructure.

Variable cost rationale

Cost scales with the volume of memory add and retrieval requests, which grows with conversation and agent traffic, and add operations involve an LLM call to extract facts, so high write workloads consume quota and cost faster. Self hosting shifts cost to your own infrastructure.

Additional watchouts

Add requests are metered and each involves an LLM call, so high-write chat workloads consume quota and cost quickly. Graph memory and Dream are Pro and above; on-prem, audit logs and SSO are Enterprise only.

Overage / add-ons

Plans cap monthly add and retrieval requests by tier; exceeding a tier's quota means upgrading, and the company also offers usage based pricing for needs that do not fit a tier. Self hosting the open source build carries no request metering.

Sales call required

No, self serve available

Free / trial

Free Hobby tier: 10,000 add and 1,000 retrieval requests/month, 1 project, community support. Open source (Apache 2.0) and self hostable at no license cost.

Lowest paid plan

Starter $19/mo (50k add, 5k retrieval requests/mo)

Commercial notes

Open-source-led, developer-first adoption with a free tier and a free Apache 2.0 self-hosting path, scaling to managed tiers and an Enterprise plan for on-prem, SSO and audit logs.

Key ambiguities

Enterprise dollar pricing and usage based per request rates above plan quotas are not public.

Cancellation / refund

Hobby, Starter, Growth, and Pro are self serve subscriptions with standard cancellation. Enterprise terms are contractual.

Support SLA / resale

Community support on Hobby and Starter, email on Growth, private Slack on Pro, and private Slack with an SLA on Enterprise.

Missing data

Enterprise dollar pricing and the exact usage based per request rates are not public.

Agentic Index verified 2026-09-21

Official pricing page

Related vendors

Alternatives to Mem0

The closest documented capability profiles to Mem0 among agent infrastructure platforms tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.

Zep7.0 / 14Adds documented Knowledge Grounding & RAGMem0 vs Zep →
Cognee7.0 / 14Adds documented Workflow Orchestration and Knowledge Grounding & RAGMem0 vs Cognee →
Hyperspell7.0 / 14Adds documented Knowledge Grounding & RAG and Testing, Debugging & Optimization
Deepgram7.5 / 14Adds documented Workflow Orchestration and Human Oversight & Guardrails, among others
Rime3.5 / 14A lighter documented profile than Mem0
Speechmatics3.5 / 14A lighter documented profile than Mem0

Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded

Compare Mem0 with other vendors →Compare all agent infrastructure platforms →See where Mem0 ranks →

Data confidence: high

Head to head

Mem0 vs Letta Mem0 vs Zep Mem0 vs Cognee