Expertise·AI & Agents·v3.0.0

Mem0

Mem0 Platform SDK for adding persistent memory to AI applications, covering the Python and TypeScript SDKs plus framework integrations.

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Buy it · $24 Read it before you buy $24 Written by mem0ai · unverified publisher
Context cost
30.4k tokensestimated from the bundle, loaded when it triggers
Bundle
13 files · 121.8 kB1 script among them — read before you run
Licence
Apache-2.0paid listing
Last change
v3.0.0
Servers it uses
Noneruns standalone

What it does

Mem0 Platform SDK for adding persistent memory to AI applications. TRIGGER when: user mentions "mem0", "MemoryClient", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python SDK (mem0ai), TypeScript SDK (mem0ai), and framework integrations (LangChain, CrewAI, OpenAI Agents SDK, Pipecat, LlamaIndex, AutoGen, LangGraph). Also covers the open-source self-hosted Memory class. This is the DEFAULT mem0 skill for ambiguous queries.

Installed, it changes the agent in these ways.

What this skill changes about the agent is not written down here yet. The listing was collected from its source, and the description is in its own SKILL.md.

Expertise

Domain judgement the base model does not have.

memoryagentssdkpersonalization
Filed under

AI & Agents

The skill itself

This is the whole product. A skill is instructions the model reads, so there is nothing behind the listing you cannot see first — the front matter loads with every session, and the body below it loads when the skill triggers.

SKILL.md7.8 kB · 194 lines
--- name: mem0 description: > Mem0 Platform SDK for adding persistent memory to AI applications. TRIGGER when: user mentions "mem0", "MemoryClient", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python SDK (mem0ai), TypeScript SDK (mem0ai), and framework integrations (LangChain, CrewAI, OpenAI Agents SDK, Pipecat, LlamaIndex, AutoGen, LangGraph). Also covers the open-source self-hosted Memory class. This is the DEFAULT mem0 skill for ambiguous queries. DO NOT TRIGGER when: user asks about CLI commands, terminal usage, or shell scripts (use mem0-cli), or Vercel AI SDK / @mem0/vercel-ai-provider / createMem0 (use mem0-vercel-ai-sdk). license: Apache-2.0 metadata: author: mem0ai version: "3.0.0" category: ai-memory tags: "memory, personalization, ai, python, typescript, vector-search" compatibility: Requires Python 3.10+ or Node.js 18+, pip install mem0ai or npm install mem0ai, MEM0_API_KEY env var (Platform), and internet access to api.mem0.ai. SDK v3 with v2 compatibility mode available. ---
24# Mem0 Platform Integration
25
26> **Skill Graph:** This skill is part of the Mem0 skill graph:
27> - **mem0** (this skill) -- Platform Client SDK + OSS (Python + TypeScript)
28> - **[mem0-cli](../mem0-cli/SKILL.md)** ([GitHub](https://github.com/mem0ai/mem0/tree/main/skills/mem0-cli)) -- Command-line interface
29> - **[mem0-vercel-ai-sdk](../mem0-vercel-ai-sdk/SKILL.md)** ([GitHub](https://github.com/mem0ai/mem0/tree/main/skills/mem0-vercel-ai-sdk)) -- Vercel AI SDK provider
30
31Mem0 is a managed memory layer for AI applications. It stores, retrieves, and manages user memories via API — no infrastructure to deploy. For self-hosted usage, see the OSS section in the client references below.
32
33## Step 1: Install and authenticate
34
35**Python:**
36```bash
37pip install mem0ai
38export MEM0_API_KEY="m0-your-api-key"
39```
40
41**TypeScript/JavaScript:**
42```bash
43npm install mem0ai
44export MEM0_API_KEY="m0-your-api-key"
45```
46
47Get an API key at: https://app.mem0.ai/dashboard/api-keys?utm_source=oss&utm_medium=skill-mem0
48
49> **Don't have a MEM0_API_KEY?** Run mem0 init --agent --agent-caller <your-name> --json (after pip install mem0-cli or npm install -g @mem0/cli), substituting your agent identity (e.g. claude-code, cursor). If you forgot to pass --agent-caller, run mem0 identify <your-name> after init. The human can claim later with mem0 init --email <your-email>.
50
51## Step 2: Initialize the client
52
53**Python:**
54```python
55from mem0 import MemoryClient
56client = MemoryClient(api_key="m0-xxx")
57```
58
59**TypeScript:**
60```typescript
61import MemoryClient from 'mem0ai';
62const client = new MemoryClient({ apiKey: 'm0-xxx' });
63```
64
65For async Python, use AsyncMemoryClient.
66
67## Step 3: Core operations
68
69Every Mem0 integration follows the same pattern: **retrieve → generate → store**.
70
71### Add memories
72```python
73messages = [
74 {"role": "user", "content": "I'm a vegetarian and allergic to nuts."},
75 {"role": "assistant", "content": "Got it! I'll remember that."}
76]
77client.add(messages, user_id="alice")
78```
79
80### Search memories
81```python
82results = client.search("dietary preferences", filters={"user_id": "alice"})
83for mem in results.get("results", []):
84 print(mem["memory"])
85```
86
87### Get all memories
88```python
89all_memories = client.get_all(filters={"user_id": "alice"})
90```
91
92### Update a memory
93```python
94client.update("memory-uuid", text="Updated: vegetarian, nut allergy, prefers organic")
95```
96
97### Delete a memory
98```python
99client.delete("memory-uuid")
100client.delete_all(user_id="alice") # delete all for a user
101```
102
103## Common integration pattern
104
105```python
106from mem0 import MemoryClient
107from openai import OpenAI
108
109mem0 = MemoryClient()
110openai = OpenAI()
111
112def chat(user_input: str, user_id: str) -> str:
113 # 1. Retrieve relevant memories
114 memories = mem0.search(user_input, filters={"user_id": user_id})
115 context = "\n".join([m["memory"] for m in memories.get("results", [])])
116
117 # 2. Generate response with memory context
118 response = openai.chat.completions.create(
119 model="gpt-5-mini",
120 messages=[
121 {"role": "system", "content": f"User context:\n{context}"},
122 {"role": "user", "content": user_input},
123 ]
124 )
125 reply = response.choices[0].message.content
126
127 # 3. Store interaction for future context
128 mem0.add(
129 [{"role": "user", "content": user_input}, {"role": "assistant", "content": reply}],
130 user_id=user_id
131 )
132 return reply
133```
134
135## Common edge cases
136
137- **Search returns empty:** Memories process asynchronously. Wait 2-3s after add() before searching. Also verify user_id matches exactly (case-sensitive) and use filters={"user_id": "..."} syntax.
138- **AND filter with user_id + agent_id returns empty:** Entities are stored separately. Use OR instead, or query separately.
139- **Duplicate memories:** Don't mix infer=True (default) and infer=False for the same data. Stick to one mode.
140- **Wrong import:** Always use from mem0 import MemoryClient (or AsyncMemoryClient for async). Do not use from mem0 import Memory.
141- **v3 defaults:** top_k=20, threshold=0.1, rerank=False. Adjust as needed for your use case.
142
143## v2 Compatibility
144
145If you're using SDK v2.x, note these differences:
146- **Entity IDs:** Pass user_id as top-level kwarg to search() instead of inside filters
147- **Defaults:** top_k=100, no threshold, rerank=True
148- **Graph memory:** Available via enable_graph=True
149
150See the [migration guide](https://docs.mem0.ai/migration/oss-v2-to-v3) for details.
151
152## Live documentation search
153
154For the latest docs beyond what's in the references, use the doc search tool:
155
156```bash
157python ${CLAUDE_SKILL_DIR}/scripts/mem0_doc_search.py --query "topic"
158python ${CLAUDE_SKILL_DIR}/scripts/mem0_doc_search.py --page "/platform/features/graph-memory"
159python ${CLAUDE_SKILL_DIR}/scripts/mem0_doc_search.py --index
160```
161
162No API key needed — searches docs.mem0.ai directly.
163
164## Client SDK References
165
166Language-specific deep references (Platform + OSS):
167
168| Language | File |
169|----------|------|
170| Python (MemoryClient + AsyncMemoryClient + Memory OSS) | [client/python.md](client/python.md) |
171| TypeScript/Node.js (MemoryClient + Memory OSS) | [client/node.md](client/node.md) |
172| Python vs TypeScript differences | [client/differences.md](client/differences.md) |
173
174## Platform References
175
176Load these on demand for deeper detail:
177
178| Topic | File |
179|-------|------|
180| Quickstart (Python, TS, cURL) | [references/quickstart.md](references/quickstart.md) |
181| SDK guide (all methods, both languages) | [references/sdk-guide.md](references/sdk-guide.md) |
182| API reference (endpoints, filters, object schema) | [references/api-reference.md](references/api-reference.md) |
183| Architecture (pipeline, lifecycle, scoping, performance) | [references/architecture.md](references/architecture.md) |
184| Platform features (retrieval, graph, categories, MCP, etc.) | [references/features.md](references/features.md) |
185| Framework integrations (LangChain, CrewAI, OpenAI Agents, etc.) | [references/integration-patterns.md](references/integration-patterns.md) |
186| Use cases & examples (real-world patterns with code) | [references/use-cases.md](references/use-cases.md) |
187
188## Related Mem0 Skills
189
190| Skill | When to use | Link |
191|-------|-------------|------|
192| mem0-cli | Terminal commands, scripting, CI/CD, agent tool loops | [local](../mem0-cli/SKILL.md) / [GitHub](https://github.com/mem0ai/mem0/tree/main/skills/mem0-cli) |
193| mem0-vercel-ai-sdk | Vercel AI SDK provider with automatic memory | [local](../mem0-vercel-ai-sdk/SKILL.md) / [GitHub](https://github.com/mem0ai/mem0/tree/main/skills/mem0-vercel-ai-sdk) |
194
In the file
SKILL.md889 words
Files13
LicenceApache-2.0
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈290
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
30,160
on trigger
The instruction body and 12 supporting files, read only when the skill fires.
15.2%
of a 200k window
Ten skills this size would take about 152% of the window before you open a file.
050k100k150k200k context window

30.4k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Heavy. Teams tend to install this one per project rather than globally, and load it only when the job comes up.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

Adoption
Installsnone yet
Ratingno reviews yet

The procedure it runs

The procedure has not been published here. It is in the skill’s own SKILL.md, which its author has not sent to the marketplace yet.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

It writes no files and reaches no network. All it changes is how the model reasons and writes.

What it asks for
Writes filesno
Network accessno

Read from the allowed-tools line of this skill’s own SKILL.md. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

13 files, 121.8 kB on disk. Mostly text — the instructions the model reads — with 1 script in it that your client would run only if the instructions tell it to.

  • README.md3.5 kB
  • SKILL.md7.8 kB
  • client/differences.md5.0 kB
  • client/node.md11.5 kB
  • client/python.md12.9 kB
  • references/api-reference.md4.6 kB
  • references/architecture.md11.2 kB
  • references/features.md10.6 kB
  • references/integration-patterns.md11.7 kB
  • references/quickstart.md2.9 kB
  • references/sdk-guide.md9.4 kB
  • references/use-cases.md22.5 kB
  • scripts/mem0_doc_search.py8.2 kB
What is not in it

A skill installs nothing and depends on nothing: it is a folder your client reads. This one carries 1 script beside the text, so the bundle is 13 files you can review in full before installing. The Apache-2.0 licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

$24 once
Mem0 · Apache-2.0 · mem0ai
one-time
Price$24 once
LicenceApache-2.0 — the author’s, unchanged by this purchase
Paid throughStripe, once, on the card you add at the checkout
Keeps workingfor good — the files are yours once they are on disk
Updatesevery release of 3.x through this account

You can read the whole bundle before paying — the SKILL.md above is the product, not a preview of it. What the money buys is the delivery: the folder packaged and handed to your machine by key, every update its author ships, and our support if it does not do what this listing says. The terms of use are Apache-2.0, set by the author and unchanged by buying it here.

Payment runs through Stripe, on a page like this one rather than a redirect. Once there is an account it joins the same mcprush invoice as everything else you run, so there is never a second card to enter.

Which clients pick it up on their own

A skill is a folder of text. A client with a skills folder reads it without being told; everywhere else the same text works, it is just handed to the model rather than found.

Claude Code.claude/skills/
Claude Desktop
ChatGPT
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok.grok/skills/
Zed.agents/skills/
Windsurf.windsurf/skills/
Agent SDK.claude/skills/
HTTP / API
This release
Version3.0.0
Publishedno release date on file
Price$24
Referencemem0ai/mem0

Versions

v3.0.0 is what is on the shelf; no release here carries a date. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

v3.0.0
  • No earlier releases have been published to the marketplace.
Pinning

Put mem0ai/mem0@3.0.0 in the install command to hold this exact version. Without the suffix you get whatever is current the day you install, and nothing moves under you afterwards.

Reviews

no reviews yet · no installs yet

Nobody has reviewed this skill yet. The rating is the mean of the reviews written here, so there is none until somebody writes the first.

Who can post

Only accounts that have had the skill installed for fourteen days, so a review is written after living with it rather than after reading it. Publishers may reply once.

Who wrote it

ME
mem0ai

Publishes on mcprush.

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