Fireproof JSON Document Server

The Fireproof Storage MCP Database Server addresses a common pain point for developers building AI‑powered applications: the need to persist and query structured data in a way that is both lightweight and secure. Traditional databases often require complex setup, maintenance, or scaling concerns that distract from the core AI logic. By wrapping Fireproof—a peer‑to‑peer, client‑side encrypted database—into an MCP server, the tool eliminates these overheads and gives Claude or other AI assistants instant access to a fully‑functional JSON document store.

At its core, the server exposes a straightforward CRUD API for JSON documents. Clients can create new records, retrieve existing ones by key or query, update fields, and delete entries. Beyond basic CRUD, the server supports sorting queries on any field, enabling developers to implement pagination or filtering without writing custom code. Because Fireproof encrypts data locally before it ever leaves the client machine, the server guarantees that sensitive information remains confidential while still being accessible to the AI assistant for context‑aware reasoning.

Key capabilities include:

• Secure storage: All documents are encrypted on the client side, protecting privacy even when the server is shared or hosted in untrusted environments.
• Flexible querying: Sort and filter by arbitrary JSON fields, allowing complex data retrieval patterns with minimal effort.
• MCP compatibility: The server adheres to the MCP specification, making it plug‑and‑play with Claude Desktop and other MCP‑enabled assistants.
• Minimal footprint: The implementation is lightweight, requiring only a Node.js runtime and the Fireproof library—no database server or external services.

Typical use cases span from personal knowledge bases to collaborative project management. For example, a developer can store snippets of code, configuration files, or research notes in the Fireproof database and let an AI assistant retrieve them on demand during a coding session. In a team setting, the server can act as a shared knowledge hub where each member’s contributions are encrypted and instantly available to all, facilitating rapid iteration without compromising security.

Integrating the Fireproof MCP Server into an AI workflow is straightforward: add a single entry to the assistant’s configuration file pointing to the server’s command, and the AI gains a new tool named . From there, the assistant can invoke CRUD operations as if they were native commands, enabling dynamic data manipulation within conversational flows. This tight coupling between the AI and a secure, queryable datastore unlocks powerful scenarios—such as context‑aware debugging, automated documentation generation, or real‑time analytics—that would otherwise require cumbersome manual data handling.