"Pocket" matching MCP servers:

Enables an AI assistant to keep every conversation verbatim in a local SQLite store and recall the most relevant past turns on demand, using hybrid keyword and embedding search plus time-awareness. Results are packed into a small token budget (2k–8k tokens) so long histories fit modest context windows, with secrets masked before storage.

Enables AI assistants to save, retrieve, and manage research content using ChromaDB vector storage with semantic search, topic organization, and automatic deduplication powered by OpenAI embeddings.

MCP server that allows interaction with PocketBase databases, enabling record operations (fetch, list, create, update), file management, and schema migrations through natural language.

Enables AI agents to run curated English and Chinese web searches through a single search_web MCP tool, returning each result with explicit fetched_at timestamps for grounded, provenance-aware answers.

A privacy-first personal context engine that ingests personal photos and message exports, extracts cited facts, and serves a queryable profile over MCP for natural-language questions like 'when did I last see Sarah?'.