CtxVault – Local memory control layer for multi-agent AI systems
Multi-vault isolation for agent memory when vector stores + filtering already exist.
Vaults enforce memory access control server-side, not through application code.
Multi-agent system builders, AI engineers managing shared state
Pinecone namespaces · Weaviate multi-tenancy · Qdrant role-based access
The obvious approach is a shared vector store with metadata filtering to separate what each agent can see. It works until someone writes a bug, adds a new code path, or bypasses the filter entirely — the boundary is only as strong as every line of application code that touches it.
The other thing that bothered me was visibility. Once agents start writing memory autonomously you have no idea what they actually know. If something goes wrong you're debugging a black box.
So I built something around vaults — separate directories with independent vector indexes. Access control is declared via CLI and enforced server-side on every request, independent of what the application code does. Agents write context at runtime and retrieve it semantically in future sessions without manual reindexing, and every vault is just a folder on your machine you can open, read, and edit at any time.
Fully local, pip installable.
github.com/Filippo-Venturini/ctxvault
Multi-vault isolation for agent memory when vector stores + filtering already exist.
MCP-native memory with synthetic data generation for AI agent retrieval workflows.
Vault proxy injects credentials at the network layer so agents never touch your keys.
Single binary with zero deps, but just another agent wrapper atop existing APIs.
Structured memory layers for agents—but vector search already solves this problem.
Shared memory across Claude Code, Cursor, Windsurf—solves agent drift via hybrid search and audit trails.