> ## Documentation Index > Fetch the complete documentation index at: https://docs.mem0.ai/llms.txt > Use this file to discover all available pages before exploring further. # MCP Integration > Connect any AI client to Mem0 using Model Context Protocol for universal memory access > Model Context Protocol (MCP) provides a standardized way for AI agents to manage their own memory through Mem0, without manual API calls. ## Why use MCP When building AI applications, memory management often requires manual integration. MCP eliminates this complexity by: * **Universal compatibility**: Works with any MCP-compatible client (Claude, Claude Code, Cursor, Windsurf, VS Code, OpenCode) * **Agent autonomy**: AI agents decide when to save, search, or update memories * **Zero infrastructure**: No servers to maintain - Mem0's cloud MCP handles everything * **Standardized protocol**: One integration works across all your AI tools ## Setup Add Mem0 MCP to all supported clients with a single command: ```bash theme={null} npx mcp-add \ --name mem0-mcp \ --type http \ --url "https://mcp.mem0.ai/mcp" \ --clients "claude,claude code,cursor,windsurf,vscode,opencode" ``` Or configure a specific client: ```bash theme={null} npx mcp-add \ --name mem0-mcp \ --type http \ --url "https://mcp.mem0.ai/mcp" \ --clients "cursor" ``` For manual configuration, add this to your MCP client config: ```json theme={null} { "mcpServers": { "mem0-mcp": { "type": "http", "url": "https://mcp.mem0.ai/mcp" } } } ``` For detailed per-client instructions, see the [Mem0 MCP Quickstart](/platform/mem0-mcp). ## Available tools The MCP server exposes 11 memory tools to your AI client: | Tool | Purpose | | --------------------- | ----------------------------------------------------------- | | `add_memory` | Store conversations or facts | | `search_memories` | Find relevant memories with filters | | `get_memories` | List memories with pagination | | `update_memory` | Modify existing memory content | | `delete_memory` | Remove specific memories | | `delete_all_memories` | Bulk delete memories | | `delete_entities` | Remove user/agent/app entities | | `get_memory` | Retrieve single memory by ID | | `list_entities` | View stored entities | | `list_events` | List memory operation events with filters and pagination | | `get_event_status` | Check the status of an async memory operation by `event_id` | ## How it works 1. **Configure the MCP server** - Add Mem0 MCP to your AI client using the setup command above 2. **Agent connects** - Your AI client connects to Mem0's cloud MCP server over HTTP 3. **Autonomous memory** - The agent decides when to store/retrieve memories as part of its reasoning 4. **No manual API calls** - The agent manages memory automatically through MCP tools ## Example interactions Once connected, your AI agent can: ``` User: Remember that I'm allergic to peanuts Agent: [calls add_memory] Got it! I've saved your peanut allergy. User: What dietary restrictions do I know about? Agent: [calls search_memories] You have a peanut allergy. ``` The agent automatically decides when to use memory tools based on context. ## Try these prompts ```python theme={null} # Multi-task operations "Generate 5 user personas for our e-commerce app with different demographics, store them all, then search for existing personas" # Natural context retrieval "Anything about my work preferences I should remember?" # Complex information updates "Update my current project: the mobile app is now 80% complete, we've fixed the login issues, and the launch date is March 15" # Time-based queries "What meetings did I have last week about Project Phoenix?" # Memory cleanup "Delete all test data and temporary memories from our development phase" # Personal preferences "I drink oat milk cappuccino with one sugar every morning, and I prefer standing desks" # Health and wellness tracking "I'm allergic to peanuts and shellfish, and I go for 5km runs on weekday mornings" ``` These examples demonstrate how MCP enables natural language memory operations - the AI agent automatically determines when to add, search, update, or delete memories based on context. ## What you can do The Mem0 MCP server enables powerful memory capabilities for your AI applications: * **Health tracking**: "I'm allergic to peanuts and shellfish" - Add new health information * **Research data**: "Store these trial parameters: 200 participants, double-blind, placebo-controlled" - Save structured data * **Preference queries**: "What do you know about my dietary preferences?" - Search and retrieve relevant memories * **Project updates**: "Update my project status: the mobile app is now 80% complete" - Modify existing memory * **Data cleanup**: "Delete all memories from 2023" - Bulk remove outdated information * **Topic overview**: "Show me everything about Project Phoenix" - List all memories for a subject ## Performance tips * Use specific filters when searching large memory sets * Batch operations when adding multiple memories * Monitor memory usage in the Mem0 dashboard ## Best practices * **Use the cloud MCP**: The hosted MCP server at `https://mcp.mem0.ai/mcp` handles infrastructure for you * **Use wildcards**: `user_id: "*"` to search across all users * **Monitor usage**: Track memory operations in the dashboard * **Document patterns**: Share successful prompt patterns with your team