Save Context from MCP Bloat
Caches bloated MCP responses and lets agents query with jq, saving real tokens.
Own your personal context. Let AI agents query it.
Scoped, revocable AI agent access to encrypted personal data—solves real password/context sprawl problem.
Users integrating multiple AI agents; people concerned about data privacy and repeated context-sharing across applications.
1Password (password manager with agent integrations) · Bitwarden (encrypted vault) · Infisical (secrets management with shared access)
Personal Vault is an encrypted local store for personal data with an MCP server so AI agents can query it with scoped access. You own the keys, the data never leaves your machine unless you allow it.
This isn't about agents talking to agents. It's about making the agent that works for you actually know who you are — with your permission, on your terms.
Use cases that click immediately: - Travel booking: agent pulls passport, loyalty numbers, seat pref, TSA PreCheck, dietary requirements - Form filling: government forms, insurance, visa docs — agent fills 90% of the fields from your vault
Technical details: - AES-256-GCM per field, Argon2id KDF, HKDF subkeys per category - Sensitivity tiers control what agents can see (public → standard → sensitive → critical) - Every access is audit-logged, tokens are scoped and revocable - Written in Go, no CGO, single binary, ~2500 lines
Install: curl -fsSL https://www.personalvault.dev/install.sh | sh GitHub: https://github.com/lovincyrus/personal-vault
Caches bloated MCP responses and lets agents query with jq, saving real tokens.
Postgres MCP server that lets agents inspect column values before writing queries.
Netlist navigation for AI agents beats grep 17/17 with 5x fewer tokens.
Cross-project memory for coding agents, but MCP ecosystem is nascent and fragmentation risk high.
Direct encrypted agent tunnels eliminate human copy-paste between Claude instances.
26 MCP tools for Obsidian with OAuth and remote Docker deployment.