
Migrate mem0 OSS to Platform
FreeSeamlessly transition your mem0 setup to the hosted platform.
Free · Opens the source repo
What Migrate mem0 OSS to Platform does
The Migrate mem0 OSS to Platform skill is designed to assist developers in transitioning their projects from the self-hosted mem0 open-source SDK to the hosted mem0 Platform SDK. This migration is essential for developers who want to leverage the benefits of a managed service while maintaining their existing project structure. The skill identifies where mem0 is utilized within the codebase, generates a detailed migration plan, and executes the changes upon approval, ensuring a smooth transition without disrupting the project's functionality.
The migration process begins with a comprehensive analysis of the existing mem0 implementation. It discovers every instance of mem0 usage, including imports, configuration blocks, and method calls. This thorough examination ensures that no critical aspects are overlooked, which could lead to runtime issues post-migration. The skill then verifies the API signatures of both the OSS and hosted SDKs to ensure compatibility, preventing potential errors during the migration.
Once the analysis is complete, the skill maps the existing calls to their hosted equivalents, flagging any discrepancies that require developer attention. This includes changes in method signatures and any potential impacts on existing functionality. The final step involves drafting a migration plan that outlines the necessary changes, which the developer can review before any code modifications are made. This structured approach minimizes risks and maintains the integrity of the project throughout the migration process.
This skill is particularly beneficial for developers who are currently using the self-hosted mem0 SDK and are looking to simplify their infrastructure by moving to a cloud-based solution. It is especially useful for projects that rely heavily on mem0 for memory management and want to avoid the complexities of maintaining local infrastructure.
When to use it
Use this skill when you need to migrate your mem0 integration from a self-hosted environment to the managed mem0 Platform, especially if you want to simplify your infrastructure.
When not to use it
This skill is not suitable for projects that do not currently use mem0 or for those looking to refactor unrelated code during the migration process.
What you can build with it
Transitioning to Managed Services
A developer wants to simplify their infrastructure by moving from a self-hosted mem0 setup to the hosted mem0 Platform.
Updating API Integrations
A team is looking to update their existing mem0 API integrations to take advantage of the latest hosted features without disrupting their current workflow.
Streamlining Project Dependencies
A project with multiple local dependencies for mem0 seeks to reduce complexity by migrating to the hosted solution.
How to install Migrate mem0 OSS to Platform
View source1. Install with the skills CLI
npx skills add mem0ai/mem0/mem0-oss-to-platform --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by mem0aiMigrate mem0 OSS → mem0 Platform (hosted)
This skill migrates a project's memory layer from the self-hosted mem0 OSS SDK to the hosted mem0 Platform SDK, working for any project shape — an agent, a RAG pipeline, an API service, a chatbot, a background worker. You discover where mem0 is actually used, write a plan the developer reviews, and then execute it on approval.
The mental model (read this first — it's why the migration is shaped the way it is)
OSS mem0 means the developer runs the whole memory stack themselves: a vector store
(Qdrant/pgvector/Chroma/…), an embedder, an LLM for fact extraction, and a local history DB. All of
that is wired up in a config object passed to Memory.
The Platform means mem0 runs that stack for them. The developer just holds an API key. So
the migration is mostly subtraction: the local infrastructure config collapses into a single
MemoryClient(api_key=...). The method calls stay recognizable (add/search/get_all/…), but a
few parameter conventions tighten up and the return values are server responses.
So the core of every migration is:
Memory/Memory.from_config({...})→MemoryClient()(reads the API key from the env).- Delete the local
vector_store/llm/embedder/graph_store/history_db_pathconfig. - Fix up each call site to the hosted call convention (entity IDs into
filters, pagination, etc.). - Flag everything that isn't a clean 1:1 so the developer can decide (see
references/gotchas.md).
Scope discipline: touch only mem0-related code, config, dependencies, and env. Preserve the project's existing behavior, structure, and style. Do not rename things, "tidy" nearby code, or change the app's logic. The developer asked to swap a backend, not to refactor their project.
Workflow
Work through these phases in order. Phases 1–4 produce the plan; phase 5 runs only after approval.
Phase 0 — Prerequisite check
The hosted SDK needs a mem0 API key (MEM0_API_KEY, obtainable at https://app.mem0.ai). Confirm
the developer has one. You don't need the key value to write the plan, but flag in the plan that it
must be set (in .env / secrets manager, never hardcoded) before execution and verification.
Phase 1 — Discover the mem0 footprint
Do not assume the layout. Find every place mem0 appears. Detect the language and the installed version first, then sweep for usage. Concretely, search for:
- Imports / instantiation:
from mem0 import Memory,Memory.from_config,Memory(,import ... from "mem0ai",from "mem0ai/oss",new Memory(. - Config blocks: keys like
vector_store/vectorStore,embedder,llm,graph_store/graphStore,history_db_path,historyStore,custom_fact_extraction_prompt,custom_update_memory_prompt,enable_graph. - Every call site:
.add(,.search(,.get_all(/.getAll(,.delete_all(/.deleteAll(,.get(,.update(,.delete(,.reset(,.history(. - Dependencies & env:
requirements.txt/pyproject.toml/package.jsonformem0aiand any local-infra deps that exist only for mem0 (e.g.qdrant-client,chromadb);.env/config for things likeOPENAI_API_KEYused by the local embedder/LLM; any docker-compose service (e.g. a Qdrant container) that exists only to back mem0.
Use Grep/Glob broadly; a single missed call site is a runtime break later. Record file:line for
each finding — the plan's inventory is built from this.
Phase 2 — Verify the API against the installed SDK (don't guess)
Versions drift, and the OSS and hosted classes have subtly different signatures. Before mapping, confirm the real signatures of the installed package rather than trusting memory:
- Python:
python -c "import inspect; from mem0 import MemoryClient; print(inspect.signature(MemoryClient.search))"for each method you'll touch, and read the installed source undersite-packages/mem0/client/main.pyif anything is ambiguous (e.g. whether a method rejects top-level entity params). Also check the OSS side the project currently uses. - TypeScript: read the installed types/dist under
node_modules/mem0ai/to confirm option names (limitvstopK,userIdvs a nestedfilters) and the default vsmem0ai/ossexport.
This verification step is the single most important habit — it's what keeps the plan correct across
mem0 versions. Then consult references/api-mapping.md for the OSS→hosted translation of each
method (Python and TypeScript), and the official guide at https://docs.mem0.ai/migration/oss-v2-to-v3.
Phase 3 — Map each site and flag the gaps
For every call site and config block from Phase 1, determine the hosted equivalent using the
mapping. Most calls map cleanly. Some don't — and those matter more than the mechanical edits.
Read references/gotchas.md and flag anything that needs a human decision: self-hosted/data-
residency setups, local model choices moving server-side, graph-memory usage, custom prompts, hot-
path calls that now make network round-trips, and existing locally-stored memories not carrying
over (data migration is out of scope unless the developer asks — note it, don't silently attempt it).
Phase 4 — Write the plan and stop
Write the full plan to MEM0_MIGRATION_PLAN.md at the repo root, following the structure in
references/plan-template.md. It must be concrete enough to execute from and honest about the gaps.
Then stop and present it for review. Do not start editing code in the same turn — the whole
point is that the developer reads and approves the plan first.
Phase 5 — Execute on approval (guided)
Once the developer approves (they may ask for changes first — incorporate them), execute the plan:
- Make the edits file by file, staying strictly within mem0 scope.
- Update dependencies and env (
MEM0_API_KEY; remove now-dead local-infra deps/services only if they exist solely for mem0 and you're confident). - Verify, mirroring how you'd confirm any backend swap:
- It imports / type-checks / byte-compiles.
- A smoke test exercises
add→search/get_all→delete_allagainst the hosted API with a realMEM0_API_KEY, and the app's own entry point still runs. - No local mem0 storage directory gets created anymore (e.g. a
.mem0/, local Qdrant path) — proof the memory really lives on the platform now.
- Report what changed, what was verified, and any flagged concerns the developer still needs to act on (e.g. configuring custom instructions in the dashboard, migrating old data).
Reference files
references/api-mapping.md— exact OSS→hosted method/param/return mapping for Python and TypeScript, plus dependency and env changes. Read during Phase 2–3.references/gotchas.md— the things that aren't a clean 1:1 and need a human decision. Read during Phase 3 so the plan's "Concerns" section is complete.references/plan-template.md— the exact structure forMEM0_MIGRATION_PLAN.md. Use in Phase 4.
Frequently asked questions about Migrate mem0 OSS to Platform
Similar skills
WinMD API Search
Easily find and explore Windows desktop APIs.
WebMCPify
Transform any web app into an agent-ready platform.
Phoenix Tracing
Instrument LLM applications with OpenInference tracing.
Foundry Hosted Agent CopilotKit
Guidance for developing agentic web apps on Azure.
Power Automate Foundation
Connect AI agents to Power Automate seamlessly.
Power Automate Flow Builder
Efficiently build and deploy Power Automate flows programmatically.
