VibeXP
← FeaturesMemoryThe context your AI builds on

Your AI forgets. This does not.

Memory is where your AI writes down what it learns and reads it back before the next task. Every session starts smarter than the last, in every tool you use, for everyone on your team.

The problem.

Without it
01

Every session starts cold

You re-describe the project, the stack and the standards to every tool, every time.

02

Nothing carries over

What your AI worked out yesterday is gone today, and you become its memory, copying context from chat to chat.

03

Built-in memory is locked in

Claude's memory does not help in Cursor. Context is trapped per app and per account, never shared with your team.

How it works.

Memory
Read, work, write backMemory over MCP ↗

Two explicit steps, over MCP

Before a task your agent searches memory by meaning and pulls the relevant context. As it works, it writes new lessons back. VibeXP does not watch your sessions: your AI reads and writes deliberately.

  • Indexed on save. A new memory is embedded the moment it is stored, so the next search finds it.
  • Linked to what it explains. Relate a memory to the artifact or blueprint it is about.
vibexp_io_create_memory(
  text: "Postgres pool maxes out at 20 under load.
         pool_max 50 fixed the timeouts.",
  labels: ["postgres", "perf"]
)
Find by meaningSemantic search ↗

Search context, not keywords

Semantic search finds the right memory when you do not remember the words, across memories, prompts, blueprints and artifacts. It is the same retrieval your agents call before they work.

  • No title, no template. A memory is free-form Markdown plus metadata, scoped to a project.
  • Version history. Every change is attributed; compare versions and restore safely.
vibexp_io_search(query: "why do requests time out?")
# memory    Postgres pool maxes out at 20...   0.93
# blueprint backend statement timeouts...      0.71
Frequently askedAll documentation ↗
How does my AI actually remember?

Two explicit steps over MCP. Before a task, your agent searches memory by meaning and pulls the relevant context. As it works, it writes new lessons back through the memory tools. The only automatic part is indexing: a memory is embedded the moment it is saved.

In the docs ↗
How is this different from the memory built into Claude or ChatGPT?

Built-in memory lives inside one tool and one account. VibeXP memory is shared across every tool you use, and across everyone on your team, so context never gets stranded in one app.

In the docs ↗
What can I store as a memory?

Anything worth remembering: a fact, a decision, a snippet, a preference, a lesson learned. A memory is free-form text plus metadata, scoped to a project, with no title required.

In the docs ↗
One click, and it helps more than you would think

Star the repo

Stars are how the next person tired of re-explaining their project to an AI finds this. It is the whole of the distribution: no ad budget, no sales team, no hosted plan to upsell.

Star on GitHub

Give your AI a memory that grows with you.

Free, open source and self-hosted. One command to run it, one to connect your AI tools, and everything else in the docs.