A local Python + SQLite MCP memory service that stores persona, shared experiences, facts, agreements, and unfinished work, then restores them within a context budget so a new model can continue the same conversation. It supports offline original-text persistence, Chinese keyword retrieval, provenance-tracked memories, persona versioning/rollback, and progressive fading of older events.

Enables local creation and querying of projects, storage and retrieval of source text, reading and saving storyboard tables with revision-conflict protection, and Excel export through MCP tools backed by SQLite.

Exposes a governed dbt MetricFlow semantic layer to AI agents through three tools — list metrics, list dimensions and query metrics — so questions about federal contract spend are answered from defined metrics rather than raw tables. Guardrails reject undefined metrics, raw columns, SQL in filters and bulk exports, and no tool can execute SQL.

A Claude Code plugin that gives Claude persistent memory across sessions — stores lessons and decisions as markdown in your Obsidian vault, searches them with SQLite FTS5, and mines past transcripts automatically.

Enables AI assistants to read and write a local-first SQLite memory vault from inside a chat — orienting on inherited context, searching and fetching past decisions and notes, wandering linked memories, and recording new ones on demand. All data stays on the user's machine, shared across local and cloud tools via MCP.

Enables Claude to answer plain-English questions by listing and describing database tables, running read-only SQL queries, and searching a folder of policy documents.