Graphiti is free and open source. It's MCP server works with any MCP client, from Cursor to Claude, too...
Graphiti MCP has tens of thousands of users. They deploy it to their desktops, servers, you name it. And for many different use cases: B2B, B2C, and personal use.
There are definitely potential security issues with memory for coding agents, which apply to not only Cursor but also Windsurf. Looking forward to more research in this area.
I used Claude 3.7 Sonnet for the Cursor Agent when building the demo. Happy to hop on a call to walk through your experience, as I'm surprised the agent performed so poorly. daniel AT getzep.com
We built Graphiti's MCP server for many different use cases. It's a great enhancement to Cursor, but may not offer significant value for your use case. No offense taken.
Graphiti MCP can recall more than just preferences and coding styles. Application specifications and evolution of these may be stored. For any non-trivial application, config files would likely be a misfit for this use ase.
Correct. The Graphiti MCP server, with the help of the agent, stores and retrieves preferences and requirements automatically without requiring rule changes.
I'm not actually sure. Using Cursor Rules, you may be able to instruct the agent to be explicit as to which project a memory is related to. And do the same with retrieval i.e. tell the agent to rerank search results by distance from the project node. The Tools are all there for the agent to use. Compliance likely depends on the Cursor Rules and the model used.
You can override the default OpenAI url using an environment variable (iirc, OPENAI_API_BASE). Any LLM provider / inference server offering an OpenAI-compatible API will work.
You may want to take a look at Graphiti, which accepts plaintext or JSON input and automatically constructs a KG. While it’s primarily designed to enable temporal use cases (where data changes over time), it works just as well with static content.
The PlasticList site explores safety levels, including a discussion of aggregate levels across products and chemicals. It’s an interesting but frustrating read.
You could achieve this with a single graph. Graphiti has a "message" EpisodeType that expects transcripts in a "<user>: <content>" format. When using this EpisodeType, Graphiti pays careful attention to "users," creating nodes for them and maintaining "fact" context for each user subgraph.
"Facts" shared across all users will also be updated universally. Alongside Graphiti's search, you'd be able to use cypher to query Neo4j to, for example, find hub nodes (aka highly-connected nodes), identifying common beliefs.
Graphiti MCP has tens of thousands of users. They deploy it to their desktops, servers, you name it. And for many different use cases: B2B, B2C, and personal use.
More here: https://github.com/getzep/graphiti
Source: me, one of the authors of Graphiti :-)