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Mem0 MCP
A memory system using mem0 for AI applications. Enables long-term memory for AI agents as a drop-in MCP server.
Install
npx -y @smithery/cli install @pinkpixel-dev/mem0-mcp-server --client claudeclaude mcp add mem0-mcp -- npx -y @smithery/cli install @pinkpixel-dev/mem0-mcp-server --client claude{
"mcpServers": {
"mem0-mcp": {
"command": "npx",
"args": [
"-y",
"@smithery/cli",
"install",
"@pinkpixel-dev/mem0-mcp-server",
"--client",
"claude"
]
}
}
}Install command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →@pinkpixel/mem0-mcp MCP Server ✨
A Model Context Protocol (MCP) server that integrates with Mem0.ai to provide persistent memory capabilities for LLMs. It allows AI agents to store and retrieve information across sessions.
This server uses the mem0ai Node.js SDK for its core functionality.
Features 🧠
Modernized & Advanced Tools (v0.8.0)
add_memory: Stores a memory from text content or structured message arrays.- Inputs:
content(string) ormessages(array of role/content objects),userId(string),runId/sessionId(string),agentId(string),appId(string),metadata(object),infer(boolean),customInstructions(string),waitForCompletion(boolean, default: true),timeoutMs(number, default: 15000) - Behavior: Cloud V3 additions are asynchronous. By default, this tool polls the background queue until completed. Pass
waitForCompletion: falseto get theeventIdimmediately.
- Inputs:
search_memories: Searches memories using semantic and BM25 hybrid filters.- Inputs:
query(string),userId(string),runId/sessionId(string),agentId(string),appId(string),filters(object),threshold(number),topK(number),rerank(boolean),referenceDate(string) - Behavior: Automatically nests scope variables inside the V3
filtersblock to prevent API validation errors.
- Inputs:
search_memory: Backward-compatible alias forsearch_memories.list_memories: Paginated listing of memory records scoped by identifiers.- Inputs:
userId(string),runId/sessionId(string),agentId(string),appId(string),filters(object),page(number),pageSize(number)
- Inputs:
get_memory: Retrieves a single memory record by its ID.- Inputs:
memoryId(string)
- Inputs:
update_memory: Modifies the text or metadata of an existing memory.- Inputs:
memoryId(string),text(string),metadata(object)
- Inputs:
delete_memory: Deletes a specific memory record by ID.- Inputs:
memoryId(string)
- Inputs:
get_memory_history: Retrieves the audit trail of memory revisions (cloud only).- Inputs:
memoryId(string)
- Inputs:
get_memory_capabilities: Exposes the feature matrix and support flags of the active backend storage mode.- Inputs: None
batch_update_memories: Performs bulk updates of text contents for multiple memories (cloud only).- Inputs:
updates(array of{ memoryId: string, text: string }objects)
- Inputs:
batch_delete_memories: Performs bulk deletions of multiple memories.- Inputs:
memoryIds(array of strings),confirm(boolean, must betrueto execute)
- Inputs:
rate_memory: Submits quality feedback evaluation for a memory record (cloud only).- Inputs:
memoryId(string),feedback(string:positive,negative,very_negative),reason(string, optional)
- Inputs:
get_memory_event: Manually retrieves details of a specific background event job (cloud only).- Inputs:
eventId(string)
- Inputs:
list_memory_events: Lists history logs of background memory processing events (cloud only).- Inputs:
page(number),pageSize(number)
- Inputs:
create_memory_export: Initiates an asynchronous memory export query job (cloud only).- Inputs:
schema(object),filters(object, optional),exportInstructions(string, optional)
- Inputs:
- **`get_memor
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