# Mem0

> Mem0 is a self-improving memory layer for LLM applications, enabling personalized AI experiences that retain context across sessions, adapt over time, and reduce costs by intelligently storing and retrieving relevant information.

Mem0 provides both a managed platform and open-source solutions for adding persistent memory to AI agents and applications. Unlike traditional RAG systems that are stateless, Mem0 creates stateful agents that remember user preferences, learn from interactions, and evolve behavior over time.

Key differentiators:
- **Stateful vs Stateless**: Retains context across sessions rather than forgetting after each interaction
- **Intelligent Memory Management**: Uses LLMs to extract, filter, and organize relevant information
- **Dual Storage Architecture**: Combines vector embeddings with graph databases for comprehensive memory
- **Sub-50ms Retrieval**: Lightning-fast memory lookups for real-time applications
- **Multimodal Support**: Handles text, images, and documents seamlessly

## Getting Started

- [Introduction](https://docs.mem0.ai/introduction): Overview of Mem0's memory layer for AI agents, including stateless vs stateful agents and how memory fits in the agent stack
- [Platform Overview](https://docs.mem0.ai/platform/overview): Managed solution with 4-line integration, sub-50ms latency, and intuitive dashboard
- [Vibe Code with Mem0](https://docs.mem0.ai/vibecoding): Single entry point for developers using AI coding tools (Claude Code, Cursor, Windsurf) with Mem0
- [Mem0 MCP Server](https://docs.mem0.ai/platform/mem0-mcp): Model Context Protocol server for integrating Mem0 with AI coding assistants
- [Platform vs Open Source](https://docs.mem0.ai/platform/platform-vs-oss): Compare managed platform vs self-hosted options
- [Platform Quickstart](https://docs.mem0.ai/platform/quickstart): Get started with Mem0 Platform (managed) in minutes
- [Open Source Overview](https://docs.mem0.ai/open-source/overview): Self-hosted solution with full infrastructure control and customization
- [Open Source Python Quickstart](https://docs.mem0.ai/open-source/python-quickstart): Get started with Mem0 Open Source using Python
- [Open Source Node.js Quickstart](https://docs.mem0.ai/open-source/node-quickstart): Get started with Mem0 Open Source using Node.js

## Core Concepts

- [Memory Types](https://docs.mem0.ai/core-concepts/memory-types): Working memory (short-term session awareness), factual memory (structured knowledge), episodic memory (past conversations), and semantic memory (general knowledge)
- [Memory Operations - Add](https://docs.mem0.ai/core-concepts/memory-operations/add): How Mem0 processes conversations through information extraction, conflict resolution, and dual storage
- [Memory Operations - Search](https://docs.mem0.ai/core-concepts/memory-operations/search): Retrieval of relevant memories using semantic search with query processing and result ranking
- [Memory Operations - Update](https://docs.mem0.ai/core-concepts/memory-operations/update): Modifying existing memories when new information conflicts or supplements stored data
- [Memory Operations - Delete](https://docs.mem0.ai/core-concepts/memory-operations/delete): Removing outdated or irrelevant memories to maintain memory quality

## Platform Features

- [Platform Features Overview](https://docs.mem0.ai/platform/features/platform-overview): High-level overview of all Mem0 Platform capabilities
- [Advanced Memory Operations](https://docs.mem0.ai/platform/advanced-memory-operations): Sophisticated memory management techniques for complex applications

### Essential Features
- [V2 Memory Filters](https://docs.mem0.ai/platform/features/v2-memory-filters): Advanced filtering and querying capabilities for memories
- [Entity-Scoped Memory](https://docs.mem0.ai/platform/features/entity-scoped-memory): Organize memories by user, agent, app, and session identifiers
- [Async Client](https://docs.mem0.ai/platform/features/async-client): Non-blocking operations for high-concurrency applications
- [Async Mode Default Changes](https://docs.mem0.ai/platform/features/async-mode-default-change): Understanding new async behavior defaults
- [Multimodal Support](https://docs.mem0.ai/platform/features/multimodal-support): Integration of images and documents (JPG, PNG, MDX, TXT, PDF) via URLs or Base64
- [Custom Categories](https://docs.mem0.ai/platform/features/custom-categories): Define domain-specific categories to improve memory organization

### Advanced Features
- [Graph Memory](https://docs.mem0.ai/platform/features/graph-memory): Build and query relationships between entities for contextually relevant retrieval
- [Graph Threshold](https://docs.mem0.ai/platform/features/graph-threshold): Configure graph relationship sensitivity and strength
- [Advanced Retrieval](https://docs.mem0.ai/platform/features/advanced-retrieval): Enhanced search with keyword search, reranking, and filtering capabilities
- [Criteria-Based Retrieval](https://docs.mem0.ai/platform/features/criteria-retrieval): Targeted memory retrieval using custom criteria
- [Contextual Add](https://docs.mem0.ai/platform/features/contextual-add): Add memories with enhanced context awareness
- [Custom Instructions](https://docs.mem0.ai/platform/features/custom-instructions): Customize how Mem0 processes and stores information

### Data Management
- [Direct Import](https://docs.mem0.ai/platform/features/direct-import): Bulk import existing data into Mem0 memory
- [Memory Export](https://docs.mem0.ai/platform/features/memory-export): Export memories in structured formats using customizable Pydantic schemas
- [Timestamp Support](https://docs.mem0.ai/platform/features/timestamp): Temporal memory management with time-based queries
- [Expiration Dates](https://docs.mem0.ai/platform/features/expiration-date): Automatic memory cleanup with configurable expiration

### Integration Features
- [Webhooks](https://docs.mem0.ai/platform/features/webhooks): Real-time notifications for memory events
- [Feedback Mechanism](https://docs.mem0.ai/platform/features/feedback-mechanism): Improve memory quality through user feedback
- [Group Chat Support](https://docs.mem0.ai/platform/features/group-chat): Multi-conversation memory management
- [MCP Integration](https://docs.mem0.ai/platform/features/mcp-integration): Model Context Protocol integration for AI coding tools

### Support & Migration
- [FAQs](https://docs.mem0.ai/platform/faqs): Frequently asked questions about Mem0 Platform
- [Contribute Guide](https://docs.mem0.ai/platform/contribute): Contributing to Mem0 Platform development
- [OSS to Platform Migration](https://docs.mem0.ai/migration/oss-to-platform): Guide for migrating from open-source to managed platform
- [V0 to V1 Migration](https://docs.mem0.ai/migration/v0-to-v1): Upgrading from Mem0 v0 to v1
- [Breaking Changes](https://docs.mem0.ai/migration/breaking-changes): List of breaking changes across versions
- [API Changes](https://docs.mem0.ai/migration/api-changes): Detailed API changes and migration paths

## Open Source

### Getting Started
- [Python Quickstart](https://docs.mem0.ai/open-source/python-quickstart): Installation, configuration, and usage examples for Python SDK
- [Node.js Quickstart](https://docs.mem0.ai/open-source/node-quickstart): Installation, configuration, and usage examples for Node.js SDK
- [Configuration Guide](https://docs.mem0.ai/open-source/configuration): Complete configuration options for self-hosted deployment

### Open Source Features
- [Features Overview](https://docs.mem0.ai/open-source/features/overview): Overview of all open-source features
- [Graph Memory](https://docs.mem0.ai/open-source/features/graph-memory): Build and query entity relationships using graph stores like Neo4j
- [Metadata Filtering](https://docs.mem0.ai/open-source/features/metadata-filtering): Advanced filtering using custom metadata fields
- [Reranker Search](https://docs.mem0.ai/open-source/features/reranker-search): Enhanced search results with reranking models
- [Async Memory](https://docs.mem0.ai/open-source/features/async-memory): Asynchronous memory operations for better performance
- [Multimodal Support](https://docs.mem0.ai/open-source/features/multimodal-support): Handle text, images, and documents in self-hosted setup
- [Custom Fact Extraction](https://docs.mem0.ai/open-source/features/custom-fact-extraction-prompt): Tailor information extraction for specific use cases
- [Custom Memory Update Prompt](https://docs.mem0.ai/open-source/features/custom-update-memory-prompt): Customize how memories are updated and merged
- [REST API Server](https://docs.mem0.ai/open-source/features/rest-api): FastAPI-based server with core operations and OpenAPI documentation
- [OpenAI Compatibility](https://docs.mem0.ai/open-source/features/openai_compatibility): Seamless integration with OpenAI-compatible APIs

## Components

### LLMs
- [LLM Overview](https://docs.mem0.ai/components/llms/overview): Comprehensive guide to Large Language Model integration and configuration options
- [LLM Configuration](https://docs.mem0.ai/components/llms/config): Configuration reference for LLM providers
- [OpenAI](https://docs.mem0.ai/components/llms/models/openai): Integration with OpenAI models including GPT-4
- [Anthropic](https://docs.mem0.ai/components/llms/models/anthropic): Claude model integration with advanced reasoning capabilities
- [Azure OpenAI](https://docs.mem0.ai/components/llms/models/azure_openai): Microsoft Azure hosted OpenAI models for enterprise environments
- [Ollama](https://docs.mem0.ai/components/llms/models/ollama): Local model deployment for privacy-focused applications
- [Together](https://docs.mem0.ai/components/llms/models/together): Open-source model inference platform
- [Groq](https://docs.mem0.ai/components/llms/models/groq): High-performance LPU optimized models for fast inference
- [LiteLLM](https://docs.mem0.ai/components/llms/models/litellm): Unified LLM interface and proxy
- [Mistral AI](https://docs.mem0.ai/components/llms/models/mistral_AI): Mistral model integration
- [Google AI](https://docs.mem0.ai/components/llms/models/google_AI): Gemini model integration for multimodal applications
- [AWS Bedrock](https://docs.mem0.ai/components/llms/models/aws_bedrock): Enterprise-grade AWS managed model integration
- [DeepSeek](https://docs.mem0.ai/components/llms/models/deepseek): Advanced reasoning models
- [MiniMax](https://docs.mem0.ai/components/llms/models/minimax): MiniMax model integration
- [xAI](https://docs.mem0.ai/components/llms/models/xAI): xAI Grok models integration
- [Sarvam](https://docs.mem0.ai/components/llms/models/sarvam): Indian language models
- [LM Studio](https://docs.mem0.ai/components/llms/models/lmstudio): Local model management and deployment
- [LangChain LLM](https://docs.mem0.ai/components/llms/models/langchain): LangChain LLM integration
- [vLLM](https://docs.mem0.ai/components/llms/models/vllm): High-performance inference framework

### Vector Databases
- [Vector Database Overview](https://docs.mem0.ai/components/vectordbs/overview): Guide to supported vector databases for semantic memory storage
- [Vector Database Configuration](https://docs.mem0.ai/components/vectordbs/config): Configuration reference for vector database providers
- [Qdrant](https://docs.mem0.ai/components/vectordbs/dbs/qdrant): High-performance vector similarity search engine
- [Chroma](https://docs.mem0.ai/components/vectordbs/dbs/chroma): AI-native open-source vector database optimized for speed
- [PGVector](https://docs.mem0.ai/components/vectordbs/dbs/pgvector): PostgreSQL extension for vector similarity search
- [Milvus](https://docs.mem0.ai/components/vectordbs/dbs/milvus): Open-source vector database for AI applications at scale
- [Pinecone](https://docs.mem0.ai/components/vectordbs/dbs/pinecone): Managed vector database with serverless and pod deployment options
- [MongoDB](https://docs.mem0.ai/components/vectordbs/dbs/mongodb): Document database with vector search capabilities
- [Azure AI Search](https://docs.mem0.ai/components/vectordbs/dbs/azure): Microsoft's enterprise search service
- [Azure MySQL](https://docs.mem0.ai/components/vectordbs/dbs/azure_mysql): Azure Database for MySQL with vector search
- [Redis](https://docs.mem0.ai/components/vectordbs/dbs/redis): Real-time vector storage and search with Redis Stack
- [Valkey](https://docs.mem0.ai/components/vectordbs/dbs/valkey): Open-source Redis alternative with vector search
- [Elasticsearch](https://docs.mem0.ai/components/vectordbs/dbs/elasticsearch): Distributed search and analytics engine
- [OpenSearch](https://docs.mem0.ai/components/vectordbs/dbs/opensearch): Open-source search and analytics platform
- [Supabase](https://docs.mem0.ai/components/vectordbs/dbs/supabase): Open-source Firebase alternative with vector support
- [Upstash Vector](https://docs.mem0.ai/components/vectordbs/dbs/upstash-vector): Serverless vector database
- [Vectorize](https://docs.mem0.ai/components/vectordbs/dbs/vectorize): Vectorize vector database integration
- [Vertex AI Vector Search](https://docs.mem0.ai/components/vectordbs/dbs/vertex_ai): Google Cloud's vector search service
- [Weaviate](https://docs.mem0.ai/components/vectordbs/dbs/weaviate): Open-source vector search engine with built-in ML capabilities
- [FAISS](https://docs.mem0.ai/components/vectordbs/dbs/faiss): Facebook AI Similarity Search library
- [LangChain Vector Store](https://docs.mem0.ai/components/vectordbs/dbs/langchain): LangChain vector store integration
- [Baidu](https://docs.mem0.ai/components/vectordbs/dbs/baidu): Baidu vector database integration
- [Cassandra](https://docs.mem0.ai/components/vectordbs/dbs/cassandra): Apache Cassandra with vector search capabilities
- [S3 Vectors](https://docs.mem0.ai/components/vectordbs/dbs/s3_vectors): Amazon S3 Vectors integration
- [Databricks](https://docs.mem0.ai/components/vectordbs/dbs/databricks): Delta Lake integration for vector search
- [Neptune Analytics](https://docs.mem0.ai/components/vectordbs/dbs/neptune_analytics): AWS Neptune Analytics for graph and vector search
- [Turbopuffer](https://docs.mem0.ai/components/vectordbs/dbs/turbopuffer): High-performance serverless vector database

### Embedding Models
- [Embeddings Overview](https://docs.mem0.ai/components/embedders/overview): Embedding model configuration for semantic understanding
- [Embeddings Configuration](https://docs.mem0.ai/components/embedders/config): Configuration reference for embedding providers
- [OpenAI Embeddings](https://docs.mem0.ai/components/embedders/models/openai): High-quality text embeddings with customizable dimensions
- [Azure OpenAI Embeddings](https://docs.mem0.ai/components/embedders/models/azure_openai): Enterprise Azure-hosted embedding models
- [Ollama Embeddings](https://docs.mem0.ai/components/embedders/models/ollama): Local embedding models for privacy-focused applications
- [Hugging Face Embeddings](https://docs.mem0.ai/components/embedders/models/huggingface): Open-source embedding models for local deployment
- [Vertex AI Embeddings](https://docs.mem0.ai/components/embedders/models/vertexai): Google Cloud's enterprise embedding models
- [Google AI Embeddings](https://docs.mem0.ai/components/embedders/models/google_AI): Gemini embedding models
- [LM Studio Embeddings](https://docs.mem0.ai/components/embedders/models/lmstudio): Local model embeddings
- [Together Embeddings](https://docs.mem0.ai/components/embedders/models/together): Open-source model embeddings
- [LangChain Embeddings](https://docs.mem0.ai/components/embedders/models/langchain): LangChain embedder integration
- [AWS Bedrock Embeddings](https://docs.mem0.ai/components/embedders/models/aws_bedrock): Amazon embedding models through Bedrock

### Rerankers
- [Reranker Overview](https://docs.mem0.ai/components/rerankers/overview): Guide to reranking models for improving search result quality
- [Reranker Configuration](https://docs.mem0.ai/components/rerankers/config): Configuration reference for reranker providers
- [Reranker Optimization](https://docs.mem0.ai/components/rerankers/optimization): Performance tuning and optimization strategies for rerankers
- [Custom Reranker Prompts](https://docs.mem0.ai/components/rerankers/custom-prompts): Customize reranker behavior with custom prompts
- [Cohere Reranker](https://docs.mem0.ai/components/rerankers/models/cohere): Cohere reranking model integration
- [Sentence Transformer Reranker](https://docs.mem0.ai/components/rerankers/models/sentence_transformer): Cross-encoder reranking with sentence transformers
- [Hugging Face Reranker](https://docs.mem0.ai/components/rerankers/models/huggingface): Hugging Face reranking models
- [LLM Reranker](https://docs.mem0.ai/components/rerankers/models/llm_reranker): Use LLMs as rerankers for flexible relevance scoring
- [Zero Entropy Reranker](https://docs.mem0.ai/components/rerankers/models/zero_entropy): Zero Entropy reranking model

## Integrations

- [Integrations Overview](https://docs.mem0.ai/integrations): Overview of all available Mem0 integrations

### Agent Frameworks
- [LangChain](https://docs.mem0.ai/integrations/langchain): Seamless integration with LangChain framework for enhanced agent capabilities
- [LangGraph](https://docs.mem0.ai/integrations/langgraph): Build stateful, multi-actor applications with persistent memory
- [LlamaIndex](https://docs.mem0.ai/integrations/llama-index): Enhanced RAG applications with intelligent memory layer
- [CrewAI](https://docs.mem0.ai/integrations/crewai): Multi-agent systems with shared and individual memory capabilities
- [AutoGen](https://docs.mem0.ai/integrations/autogen): Microsoft's multi-agent conversation framework with memory
- [Agno](https://docs.mem0.ai/integrations/agno): Agno framework integration with persistent memory
- [Camel AI](https://docs.mem0.ai/integrations/camel-ai): Camel AI multi-agent framework with memory support
- [OpenClaw](https://docs.mem0.ai/integrations/openclaw): OpenClaw framework integration
- [OpenAI Agents SDK](https://docs.mem0.ai/integrations/openai-agents-sdk): OpenAI's agent framework with Mem0 memory
- [Google AI ADK](https://docs.mem0.ai/integrations/google-ai-adk): Google AI Agent Development Kit with persistent memory
- [Mastra](https://docs.mem0.ai/integrations/mastra): Mastra TypeScript agent framework integration
- [Vercel AI SDK](https://docs.mem0.ai/integrations/vercel-ai-sdk): Build AI-powered web applications with persistent memory

### Voice & Real-time
- [LiveKit](https://docs.mem0.ai/integrations/livekit): Real-time voice and video AI with persistent memory
- [Pipecat](https://docs.mem0.ai/integrations/pipecat): Voice AI pipeline framework with memory capabilities
- [ElevenLabs](https://docs.mem0.ai/integrations/elevenlabs): Voice synthesis integration with conversational memory

### Cloud & Infrastructure
- [AWS Bedrock](https://docs.mem0.ai/integrations/aws-bedrock): Enterprise AWS integration for managed AI services

### Developer Tools
- [Dify](https://docs.mem0.ai/integrations/dify): LLMOps platform integration for production AI applications
- [Flowise](https://docs.mem0.ai/integrations/flowise): No-code LLM workflow builder with memory capabilities
- [LangChain Tools](https://docs.mem0.ai/integrations/langchain-tools): Use Mem0 as a LangChain tool for agents
- [AgentOps](https://docs.mem0.ai/integrations/agentops): Agent observability and monitoring with memory tracking
- [Keywords AI](https://docs.mem0.ai/integrations/keywords): Keywords AI integration for LLM monitoring
- [Raycast](https://docs.mem0.ai/integrations/raycast): Raycast extension for quick memory access

## Cookbooks and Examples

- [Cookbooks Overview](https://docs.mem0.ai/cookbooks/overview): Complete guide to Mem0 examples and implementation patterns

### Essential Guides
- [Building AI Companion](https://docs.mem0.ai/cookbooks/essentials/building-ai-companion): Core patterns for building AI agents with memory
- [Partition Memories by Entity](https://docs.mem0.ai/cookbooks/essentials/entity-partitioning-playbook): Keep multi-tenant assistants isolated by tagging user, agent, app, and session identifiers
- [Controlling Memory Ingestion](https://docs.mem0.ai/cookbooks/essentials/controlling-memory-ingestion): Fine-tune what gets stored in memory and when
- [Memory Expiration](https://docs.mem0.ai/cookbooks/essentials/memory-expiration-short-and-long-term): Implement short-term and long-term memory strategies
- [Tagging and Organizing Memories](https://docs.mem0.ai/cookbooks/essentials/tagging-and-organizing-memories): Advanced memory organization and categorization
- [Exporting Memories](https://docs.mem0.ai/cookbooks/essentials/exporting-memories): Backup and transfer memory data between systems
- [Choosing Memory Architecture](https://docs.mem0.ai/cookbooks/essentials/choosing-memory-architecture-vector-vs-graph): Vector vs Graph memory architectures comparison

### AI Companion Examples
- [Quickstart Demo](https://docs.mem0.ai/cookbooks/companions/quickstart-demo): Quick demo of building an AI companion with memory
- [Node.js Companion](https://docs.mem0.ai/cookbooks/companions/nodejs-companion): JavaScript-based AI companion applications
- [AI Tutor](https://docs.mem0.ai/cookbooks/companions/ai-tutor): Educational AI that adapts to learning progress
- [Travel Assistant](https://docs.mem0.ai/cookbooks/companions/travel-assistant): Travel planning agent that learns preferences
- [YouTube Research Assistant](https://docs.mem0.ai/cookbooks/companions/youtube-research): AI that researches and learns from video content
- [Voice Companion](https://docs.mem0.ai/cookbooks/companions/voice-companion-openai): Voice-enabled AI with conversational memory
- [Local Companion](https://docs.mem0.ai/cookbooks/companions/local-companion-ollama): Privacy-focused companion using local models

### Operations & Automation
- [Support Inbox](https://docs.mem0.ai/cookbooks/operations/support-inbox): Customer service agents with conversation history
- [Email Automation](https://docs.mem0.ai/cookbooks/operations/email-automation): Smart email processing with contextual memory
- [Content Writing](https://docs.mem0.ai/cookbooks/operations/content-writing): AI writers that maintain brand voice and style
- [Deep Research](https://docs.mem0.ai/cookbooks/operations/deep-research): Research assistants that build on previous findings
- [Team Task Agent](https://docs.mem0.ai/cookbooks/operations/team-task-agent): Collaborative AI agents with shared project memory

### Integration Examples
- [Agents SDK Tool](https://docs.mem0.ai/cookbooks/integrations/agents-sdk-tool): Using Mem0 as a tool with OpenAI Agents SDK
- [OpenAI Tool Calls](https://docs.mem0.ai/cookbooks/integrations/openai-tool-calls): Mem0 integrated with OpenAI function calling
- [Mastra Agent](https://docs.mem0.ai/cookbooks/integrations/mastra-agent): Mastra framework integration with memory
- [Healthcare Google ADK](https://docs.mem0.ai/cookbooks/integrations/healthcare-google-adk): Medical AI applications with memory
- [AWS Bedrock](https://docs.mem0.ai/cookbooks/integrations/aws-bedrock): Enterprise memory with AWS managed services
- [Neptune Analytics](https://docs.mem0.ai/cookbooks/integrations/neptune-analytics): Graph and vector search with AWS Neptune
- [Tavily Search](https://docs.mem0.ai/cookbooks/integrations/tavily-search): Web search with persistent memory of results

### Framework Examples
- [LlamaIndex React](https://docs.mem0.ai/cookbooks/frameworks/llamaindex-react): React applications with LlamaIndex and memory
- [LlamaIndex Multiagent](https://docs.mem0.ai/cookbooks/frameworks/llamaindex-multiagent): Multi-agent systems with shared memory
- [Multimodal Retrieval](https://docs.mem0.ai/cookbooks/frameworks/multimodal-retrieval): Memory systems handling text, images, and documents
- [Eliza OS Character](https://docs.mem0.ai/cookbooks/frameworks/eliza-os-character): Character-based AI with persistent personality
- [Chrome Extension](https://docs.mem0.ai/cookbooks/frameworks/chrome-extension): Browser extensions that remember user interactions
- [Gemini with Mem0 MCP](https://docs.mem0.ai/cookbooks/frameworks/gemini-3-with-mem0-mcp): Google Gemini integration using MCP server
- [Mirofish Swarm Memory](https://docs.mem0.ai/cookbooks/frameworks/mirofish-swarm-memory): Swarm-based multi-agent memory patterns

## API Reference

- [API Reference Overview](https://docs.mem0.ai/api-reference): REST API overview with authentication and quick start guide
- [Organizations & Projects](https://docs.mem0.ai/api-reference/organizations-projects): Managing organizations and projects for multi-tenant setups

### Core Memory APIs
- [Add Memories](https://docs.mem0.ai/api-reference/memory/add-memories): REST API for storing new memories with detailed request/response formats
- [Get All Memories](https://docs.mem0.ai/api-reference/memory/get-memories): Retrieve all memories with pagination and filtering options
- [Search Memories](https://docs.mem0.ai/api-reference/memory/search-memories): Advanced search API with filtering and ranking capabilities
- [Update Memory](https://docs.mem0.ai/api-reference/memory/update-memory): Modify existing memories with conflict resolution
- [Delete Memory](https://docs.mem0.ai/api-reference/memory/delete-memory): Remove a specific memory by ID

### Additional Memory APIs
- [Create Memory Export](https://docs.mem0.ai/api-reference/memory/create-memory-export): Export memories in bulk
- [Feedback](https://docs.mem0.ai/api-reference/memory/feedback): Submit feedback on memory quality
- [Get Memory](https://docs.mem0.ai/api-reference/memory/get-memory): Retrieve a single memory by ID
- [Memory History](https://docs.mem0.ai/api-reference/memory/history-memory): View the history of changes to a memory
- [Get Memory Export](https://docs.mem0.ai/api-reference/memory/get-memory-export): Retrieve a previously created memory export
- [Batch Update](https://docs.mem0.ai/api-reference/memory/batch-update): Update multiple memories in a single request
- [Batch Delete](https://docs.mem0.ai/api-reference/memory/batch-delete): Delete multiple memories in a single request
- [Delete All Memories](https://docs.mem0.ai/api-reference/memory/delete-memories): Remove all memories matching criteria

### Events APIs
- [Get Events](https://docs.mem0.ai/api-reference/events/get-events): List asynchronous memory operation events
- [Get Event](https://docs.mem0.ai/api-reference/events/get-event): Retrieve details of a specific event

### Entities APIs
- [Get Users](https://docs.mem0.ai/api-reference/entities/get-users): List all entities (users, agents, apps)
- [Delete User](https://docs.mem0.ai/api-reference/entities/delete-user): Remove an entity and all associated memories

### Organizations APIs
- [Create Organization](https://docs.mem0.ai/api-reference/organization/create-org): Create a new organization
- [Get Organizations](https://docs.mem0.ai/api-reference/organization/get-orgs): List all organizations
- [Get Organization](https://docs.mem0.ai/api-reference/organization/get-org): Retrieve organization details
- [Get Organization Members](https://docs.mem0.ai/api-reference/organization/get-org-members): List organization members
- [Add Organization Member](https://docs.mem0.ai/api-reference/organization/add-org-member): Add a member to an organization
- [Delete Organization](https://docs.mem0.ai/api-reference/organization/delete-org): Remove an organization

### Project APIs
- [Create Project](https://docs.mem0.ai/api-reference/project/create-project): Create a new project within an organization
- [Get Projects](https://docs.mem0.ai/api-reference/project/get-projects): List all projects
- [Get Project](https://docs.mem0.ai/api-reference/project/get-project): Retrieve project details
- [Get Project Members](https://docs.mem0.ai/api-reference/project/get-project-members): List project members
- [Add Project Member](https://docs.mem0.ai/api-reference/project/add-project-member): Add a member to a project
- [Delete Project](https://docs.mem0.ai/api-reference/project/delete-project): Remove a project

### Webhook APIs
- [Create Webhook](https://docs.mem0.ai/api-reference/webhook/create-webhook): Register a new webhook endpoint
- [Get Webhook](https://docs.mem0.ai/api-reference/webhook/get-webhook): Retrieve webhook configuration
- [Update Webhook](https://docs.mem0.ai/api-reference/webhook/update-webhook): Modify webhook settings
- [Delete Webhook](https://docs.mem0.ai/api-reference/webhook/delete-webhook): Remove a webhook

## Community & Support

- [Contributing - Development](https://docs.mem0.ai/contributing/development): Guidelines for contributing to Mem0's open-source development
- [Contributing - Documentation](https://docs.mem0.ai/contributing/documentation): Guidelines for contributing to Mem0's documentation
- [Changelog](https://docs.mem0.ai/changelog): Detailed product updates and version history
