Memorious MCP

Overview

The Memorious MCP server fills a critical gap for developers building privacy‑first AI assistants: it delivers robust, long‑term memory capabilities without ever sending data outside the local machine. By combining ChromaDB’s disk‑based vector store with FastMCP’s lightweight protocol implementation, the server lets assistants persist facts, preferences, and contextual clues across sessions while keeping all embeddings, keys, and values strictly local. This guarantees that sensitive user information—such as personal habits or project secrets—never leaves the device, a requirement for many regulated industries and privacy‑conscious users.

At its core, Memorious exposes three intuitive tools—store, recall, and forget—that map directly onto the common memory operations needed by conversational agents. The store tool accepts a short, canonical key (1‑5 words) and an arbitrary value, automatically generating an embedding for the key and saving both to ChromaDB. Recall performs a semantic similarity search over those embeddings, returning the best‑matching value even when the query wording differs from the original key. Forget removes a stored pair by exact key match, ensuring developers can clean up stale or incorrect memories. These operations are intentionally simple so that any MCP‑compliant client can invoke them without custom code.

Key features of the server include 100 % local processing, guaranteeing that neither embeddings nor stored data ever traverse the network; persistent disk storage through ChromaDB, so memories survive reboots and client restarts; semantic search, enabling assistants to retrieve relevant information based on meaning rather than exact string matches; and folder‑scoped storage, which isolates memories per project or workspace—a boon for IDE integrations like VS Code Copilot Chat and Claude Code agents. The canonical key design further optimizes embeddings, reducing storage overhead while maintaining retrieval accuracy.

Real‑world use cases span personal assistants that remember user preferences, chatbots that maintain context across long conversations, and project‑specific knowledge bases that allow developers to query past design decisions. In privacy‑first environments—healthcare, finance, or personal data handling—the server’s local‑only model ensures compliance with strict data residency regulations. Additionally, its lightweight API and FastMCP foundation make it trivial to plug into existing MCP clients or build custom integrations, enabling developers to focus on crafting conversational logic rather than managing memory infrastructure.

In summary, Memorious MCP provides a secure, efficient, and semantically rich memory layer that empowers AI assistants to deliver consistent, personalized interactions while respecting the highest standards of data privacy and local control.