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Glama
arjunkmrm

Mem0 MCP Server

by arjunkmrm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
MEM0_API_KEYYesMem0 platform API key (required)
MEM0_DEFAULT_USER_IDNoDefault user_id injected into filters and write requests (optional)mem0-mcp
MEM0_MCP_AGENT_MODELNoDefault LLM for the bundled agent example (optional)openai:gpt-4o-mini

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
add_memoryB

Store a new preference, fact, or conversation snippet. Requires at least one: user_id, agent_id, or run_id.

search_memoriesA

Run a semantic search over existing memories.

    Use filters to narrow results. Common filter patterns:
    - Single user: {"AND": [{"user_id": "john"}]}
    - Agent memories: {"AND": [{"agent_id": "agent_name"}]}
    - Recent memories: {"AND": [{"user_id": "john"}, {"created_at": {"gte": "2024-01-01"}}]}
    - Multiple users: {"AND": [{"user_id": {"in": ["john", "jane"]}}]}
    - Cross-entity: {"OR": [{"user_id": "john"}, {"agent_id": "agent_name"}]}

    user_id is automatically added to filters if not provided.
get_memoriesA

Page through memories using filters instead of search.

    Use filters to list specific memories. Common filter patterns:
    - Single user: {"AND": [{"user_id": "john"}]}
    - Agent memories: {"AND": [{"agent_id": "agent_name"}]}
    - Recent memories: {"AND": [{"user_id": "john"}, {"created_at": {"gte": "2024-01-01"}}]}
    - Multiple users: {"AND": [{"user_id": {"in": ["john", "jane"]}}]}

    Pagination: Use page (1-indexed) and page_size for browsing results.
    user_id is automatically added to filters if not provided.
delete_all_memoriesC

Delete every memory in the given user/agent/app/run but keep the entity.

list_entitiesB

List which users/agents/apps/runs currently hold memories.

get_memoryB

Fetch a single memory once you know its memory_id.

update_memoryB

Overwrite an existing memory’s text.

delete_memoryB

Delete one memory after the user confirms its memory_id.

delete_entitiesA

Remove a user/agent/app/run record entirely (and cascade-delete its memories).

Prompts

Interactive templates invoked by user choice

NameDescription
memory_assistantGet help with memory operations and best practices.

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4/5.0

Scored across 9 tools

Disambiguation5/5

Every tool has a clearly distinct purpose with no ambiguity. For example, add_memory stores new data, get_memory retrieves a single item, get_memories pages through filtered results, and search_memories performs semantic search—each serves a unique function in the memory management workflow.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (e.g., add_memory, delete_memory, update_memory, list_entities). This uniformity makes the set predictable and easy to navigate, with no deviations in style or convention.

Tool Count5/5

With 9 tools, the server is well-scoped for memory management, covering core operations like CRUD, search, and entity handling. Each tool earns its place without feeling excessive or insufficient for the domain.

Completeness5/5

The toolset provides complete CRUD/lifecycle coverage for memory management, including add, get, update, delete, search, and entity operations. There are no obvious gaps, and agents can handle all typical workflows without dead ends.

Resources