Mem0 SDK Guide

Complete SDK reference for Python and TypeScript. All methods use MemoryClient (Platform API).

For language-specific deep references (including OSS): See client/python.md and client/node.md. For Python vs TypeScript differences: client/differences.md.

Initialization

Python:

from mem0 import MemoryClient
client = MemoryClient(api_key="m0-your-api-key")

Python (Async):

from mem0 import AsyncMemoryClient
client = AsyncMemoryClient(api_key="m0-your-api-key")

TypeScript:

import MemoryClient from 'mem0ai';
const client = new MemoryClient({ apiKey: 'm0-your-api-key' });

Constructor accepts apiKey (required) and host (optional, default: https://api.mem0.ai).

---

add() -- Store Memories

Python:

messages = [
    {"role": "user", "content": "I'm a vegetarian and allergic to nuts."},
    {"role": "assistant", "content": "Got it! I'll remember that."}
]
client.add(messages, user_id="alice")

# With metadata
client.add(messages, user_id="alice", metadata={"source": "onboarding"})

TypeScript:

await client.add(messages, { userId: "alice" });
await client.add(messages, { userId: "alice", metadata: { source: "onboarding" } });

Parameters

Advanced Add Options

# Agent + session scoping
client.add(messages, user_id="alice", agent_id="nutrition-agent", run_id="session-456")

# Raw text -- skip LLM inference
client.add(
    [{"role": "user", "content": "User prefers dark mode."}],
    user_id="alice",
    infer=False,
)

---

search() -- Find Memories

Python:

results = client.search("dietary preferences?", filters={"user_id": "alice"})

# With filters and reranking
results = client.search(
    query="work experience",
    filters={"AND": [{"user_id": "alice"}, {"categories": {"contains": "professional_details"}}]},
    top_k=5,
    rerank=True,
    threshold=0.5
)

TypeScript:

const results = await client.search("dietary preferences", { filters: { user_id: "alice" } });
const results = await client.search("work experience", {
    filters: { AND: [{ user_id: "alice" }, { categories: { contains: "professional_details" } }] },
    topK: 5,
    rerank: true,
});

Parameters

Common Filter Patterns

Python:

# Single user filter
filters={"user_id": "alice"}

# OR across agents
filters={"OR": [{"user_id": "alice"}, {"agent_id": {"in": ["travel-agent", "sports-agent"]}}]}

# Category filtering (partial match)
filters={"AND": [{"user_id": "alice"}, {"categories": {"contains": "finance"}}]}

# Category filtering (exact match)
filters={"AND": [{"user_id": "alice"}, {"categories": {"in": ["personal_information"]}}]}

# Wildcard (match any non-null run)
filters={"AND": [{"user_id": "alice"}, {"run_id": "*"}]}

# Date range
filters={"AND": [
    {"user_id": "alice"},
    {"created_at": {"gte": "2024-01-01T00:00:00Z"}},
    {"created_at": {"lt": "2024-02-01T00:00:00Z"}}
]}

# Exclude categories with NOT
filters={"AND": [{"user_id": "user_123"}, {"NOT": {"categories": {"in": ["spam", "test"]}}}]}

# Multi-dimensional query
filters={"AND": [
    {"user_id": "user_123"},
    {"keywords": {"icontains": "invoice"}},
    {"categories": {"in": ["finance"]}},
    {"created_at": {"gte": "2024-01-01T00:00:00Z"}}
]}

TypeScript:

// Single user filter
filters: { user_id: "alice" }

// OR across agents
filters: { OR: [{ user_id: "alice" }, { agent_id: { in: ["travel-agent", "sports-agent"] } }] }

// Category filtering (partial match)
filters: { AND: [{ user_id: "alice" }, { categories: { contains: "finance" } }] }

// Category filtering (exact match)
filters: { AND: [{ user_id: "alice" }, { categories: { in: ["personal_information"] } }] }

---

get() / getAll() -- Retrieve Memories

Python:

# Single memory by ID
memory = client.get(memory_id="ea925981-...")

# All memories for a user
memories = client.get_all(filters={"user_id": "alice"})

# With date range
memories = client.get_all(
    filters={"AND": [
        {"user_id": "alex"},
        {"created_at": {"gte": "2024-07-01", "lte": "2024-07-31"}}
    ]}
)

TypeScript:

const memory = await client.get("ea925981-...");
const memories = await client.getAll({ filters: { user_id: "alice" } });

Note: get_all requires at least one of user_id, agent_id, app_id, or run_id in filters.

---

update() -- Modify Memories

Python:

client.update(memory_id="ea925981-...", text="Updated: vegan since 2024")
client.update(memory_id="ea925981-...", text="Updated", metadata={"verified": True})

TypeScript:

await client.update("ea925981-...", { text: "Updated: vegan since 2024" });

---

delete() / deleteAll() -- Remove Memories

Python:

client.delete(memory_id="ea925981-...")
client.delete_all(user_id="alice")  # Irreversible bulk delete

TypeScript:

await client.delete("ea925981-...");
await client.deleteAll({ userId: "alice" });

---

history() -- Track Changes

Python:

history = client.history(memory_id="ea925981-...")
# Returns: [{previous_value, new_value, action, timestamps}]

TypeScript:

const history = await client.history("ea925981-...");

---

Batch Operations (TypeScript)

// Batch update
await client.batchUpdate([
    { memoryId: "uuid-1", text: "Updated text" },
    { memoryId: "uuid-2", text: "Another updated text" },
]);

// Batch delete
await client.batchDelete(["uuid-1", "uuid-2", "uuid-3"]);

---

Additional Methods

# List all users/agents/sessions with memories
users = client.users()

# Delete a user/agent entity
client.delete_users(user_id="alice")

# Submit feedback on a memory
client.feedback(memory_id="...", feedback="POSITIVE", feedback_reason="Accurate extraction")

# Export memories
export = client.create_memory_export(filters={"AND": [{"user_id": "alice"}]})
data = client.get_memory_export(memory_export_id=export["id"])

---

Common Pitfalls

1. Entity cross-filtering fails silently -- AND with user_id + agent_id returns empty. Use OR.
2. SQL operators rejected -- use gte, lt, etc. Not >=, <.
3. Metadata filtering is limited -- only top-level keys with eq, contains, ne.
4. Wildcard * excludes null -- only matches non-null values.
5. Default threshold is 0.1 -- increase for stricter matching.
6. Async processing -- memories process asynchronously. Wait 2-3s after add() before searching.

Naming Conventions

Python uses snake_case everywhere (user_id, memory_id, get_all). TypeScript uses camelCase for methods (getAll, deleteAll, batchUpdate) and top-level parameters (userId, topK, pageSize), but filter keys use snake_case (user_id, agent_id).

---

v2 to v3 Migration

Breaking Changes in v3

1. Entity IDs in search() and getAll()

v3 requires entity IDs (user_id, agent_id, run_id) inside filters instead of as top-level parameters:

# v2 (deprecated)
client.search("query", user_id="alice")
client.get_all(user_id="alice")

# v3
client.search("query", filters={"user_id": "alice"})
client.get_all(filters={"user_id": "alice"})

// v2 (deprecated)
await client.search("query", { user_id: "alice" });
await client.getAll({ user_id: "alice" });

// v3
await client.search("query", { filters: { user_id: "alice" } });
await client.getAll({ filters: { user_id: "alice" } });

2. TypeScript Parameter Naming

v3 TypeScript uses camelCase for all parameters:

3. Default Values Changed

4. Removed Parameters

The following parameters are no longer supported: