For a few months in 2026, openmemory mcp was the answer a lot of people gave when asked how to give Claude Desktop or Cursor a memory that survived between sessions without sending anything to the cloud. It was well-built, genuinely local, and free. It is also, as of this writing, no longer where Mem0 is putting its engineering effort, and if you were about to build on it, that matters more than the feature list does.
What OpenMemory MCP actually was
Mem0 launched OpenMemory MCP as a private, local-first memory server: a Docker container running on your own machine, backed by a self-hosted Qdrant vector store, exposing four tools over the Model Context Protocol: add_memories, search_memory, list_memories and delete_all_memories. Any MCP-capable client on the same box, Claude Desktop, Cursor, Windsurf, Cline, could call the same server and read the same memories, instead of each tool keeping its own disconnected notes about you.
The pitch was straightforward and, for a single developer's own machine, a genuinely good one. Nothing left your laptop except the calls your chosen LLM provider needed to extract and embed memories. A dashboard at localhost:3000 let you see, and delete, exactly what had been stored. Setup was a docker compose up away, and the whole thing was free beyond your own API key.
What changed in 2026
Here is the part worth knowing before you plan anything around it: the standalone mem0-mcp repository was archived on GitHub in March 2026, sixty-odd stars and several months of commits later, frozen in place. The openmemory package that had lived inside Mem0's main monorepo followed a similar path shortly after, and Mem0's current self-hosting documentation now points teams at the general-purpose Mem0 server rather than at OpenMemory specifically. The parent Mem0 project itself is very much alive, it has stayed active in 2026, well past 60,000 GitHub stars, but the local, MCP-first packaging that made OpenMemory distinct from "just run Mem0" is no longer the thing being actively developed.
None of this means the code vanished. A community fork, CaviraOSS/OpenMemory, keeps a version of the pattern alive, and Docker images built from the old source still exist on Docker Hub. What changed is who is responsible for it. An archived repository does not get security patches, does not get tested against the next breaking change in the MCP specification, and does not get a response when a client update stops working with it.
"the ecosystem is currently dominated by open-source MCP servers that are routinely cloned and deployed, and there is limited evidence on how weaknesses manifest in the code at scale across real implementations."
Academic risk-assessment framework for open-source MCP servers, arXiv, 2026
That line was written about the wider MCP server ecosystem, not about OpenMemory specifically, but it describes exactly the position an OpenMemory user is now in: running a cloned, unmaintained server, with no upstream watching for the weaknesses the paper is talking about.
Where OpenMemory MCP was actually strong
It is worth being fair to it. Local-first was the right call for a single developer wanting memory in their own coding tools without a subscription or a cloud account. The four-tool surface was small enough to reason about, the Qdrant-backed retrieval was reasonably fast, and the dashboard for auditing stored memories was a better answer to "what does this thing actually know about me" than most competitors offered at the time. For exactly the problem it targeted, one person, one machine, no shared state, it did the job cleanly.
Where it was never going to work for a company
The design that made OpenMemory MCP simple is the same one that kept it from scaling past a single user. Memories lived in one local Qdrant instance with no concept of who was asking. There was no entitlement model, because there was only ever one asker: the developer running the container. Point five different colleagues' AI tools at a shared instance and every one of them can read, and delete, everything the others stored. That is a fine trade for a personal tool. It is not a trade a company can make with its actual systems of record.
OpenMemory MCP vs the field
| Dimension | OpenMemory MCP (archived) | General Mem0 server | Contextely |
|---|---|---|---|
| Maintenance status | Standalone repo archived March 2026 | Actively maintained | Actively maintained |
| Deployment model | Local Docker, single machine | Self-hosted or Mem0 Cloud | Self-hosted via Docker or hosted |
| Multi-asker entitlement | None, single user by design | Not the core focus | Enforced inside the retrieval scoring function |
| Freshness handling | Static once stored | Depends on your own re-ingestion | Memory objects carry a TTL and re-fetch over MCP |
| Cost | Free, plus your own LLM API key | Free tier, then usage-based | Free tier, 500 retrievals/mo |
| Best fit | No longer a safe default | One developer, one assistant | A team or company with more than one asker |
Table 1: OpenMemory MCP's own design, single-user, single-machine, is the reason it never needed the entitlement or freshness work a shared company memory layer requires.
What to actually do if you were building on it
If you already have OpenMemory MCP running and it works, it will likely keep working for a while; archived does not mean it stops running today. Treat it the way you would treat any unmaintained dependency: budget for replacing it before you rely on it for anything you cannot afford to lose, and do not add new integrations against a repository nobody is patching.
If you are starting fresh and your use case is genuinely one developer wanting local memory in their own tools, the general Mem0 server is the more direct, currently maintained path, and our Mem0 vs Contextely comparison covers how the two differ where it matters.
If your actual use case was always closer to "several people, and several agents, need a shared, current, access-controlled view of what the company knows," that was never really what OpenMemory MCP was solving, single-user local memory and multi-asker company memory are different problems wearing similar marketing. That is the gap Contextely was built to close: entitlement checked at retrieval time rather than assumed away by there being only one user, memory objects with their own staleness handling instead of a static local store, and both an MCP server and MCP client so it can call back out to your systems of record when what it holds goes stale. If you are also weighing a self-hosted Glean alternative more broadly, that comparison lives here, and the practical self-hosting steps for a Docker-based memory layer are in our self-hosted AI memory setup guide.
Frequently asked people-also-ask questions
Is openmemory mcp still maintained?
Not as a standalone, actively developed product. The dedicated mem0-mcp repository was archived on GitHub in March 2026, and Mem0's own documentation now points self-hosted users at the general Mem0 server instead. Community forks exist and still run, but nobody is treating the original package as a live project.
What did openmemory mcp actually do?
It ran a local memory server, in Docker, backed by a self-hosted Qdrant vector store, exposing four tools any MCP-capable client could call: add_memories, search_memory, list_memories and delete_all_memories. A dashboard at localhost:3000 let you audit what had been stored.
What is a good openmemory mcp alternative for a team, not just one developer's laptop?
It depends on what you actually need. For the same local-first, single-user pattern with active maintenance, the general Mem0 server is the closer successor. For a shared memory layer across a company, where different people and agents are entitled to see different things, that is a different problem, and it is the one Contextely is built around.
Was openmemory mcp free?
Yes. It was open source and free to self-host, requiring only your own LLM API key for the extraction and embedding calls. There was no separate OpenMemory pricing tier; Mem0's paid plans applied to its hosted cloud product.
Can I still run openmemory mcp today?
The code is still findable in GitHub history and in at least one community fork. Nothing technically stops you running it. What you would be running is an orphaned snapshot rather than a project anyone is patching or testing against new MCP client releases.