Enables coding agents to explore a database through the project's Drizzle schema, with tools for schema inspection, row browsing, counting, read-only SQL, query plans, drift and migration checks.

Enables AI agents to store and retrieve persistent memory across sessions and machines, and to pay any x402 API while keeping a signed, offline-verifiable ledger of purchases and spending.

Enables agents to connect to and work with PostgreSQL, MySQL, Redis, SQLite, and MongoDB through a uniform tool surface for opening connections, running queries and commands, inspecting schemas, and managing documents.

Enables AI agents and LLMs to persist facts, preferences, and observations in a local SQLite store and to build and traverse subject-predicate-object knowledge graphs across sessions. It provides fuzzy keyword search and graph queries so assistants retain context and recall prior project history without repeating prompts.

Enables AI agents to look up Chinese laws and statutory articles fully offline from a local SQLite database, resolving a law name plus article number to verbatim text, searching articles by keyword, and retrieving a law's chapter structure and version history. It also verifies citations in bulk, checking whether each quoted provision exists word-for-word and is currently in force.

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.

Exposes four read-only tools over extracted Hacker News "Who is hiring?" job posts — postings_search, posting_get, skills_top, and skills_trend — so an MCP client or agent can search postings, look up individual posts, rank top skills, or chart skill trends over time. Tools return only structured extracted fields and HN links (never raw post text) from a read-only SQLite database, including salary sorting and a hard row limit to keep queries cheap.

Enables AI agents to store decisions as a versioned history, linking each new decision to the one it replaces so that recall always resolves to the decision currently in force instead of obsolete ones. It runs fully locally on a single SQLite file with BM25 search, and can optionally detect replacements automatically via an LLM or heuristic linker.

Enables AI agents to read the local, already-logged-in WeChat account's chat history: fetch recent messages per contact for reply suggestions, bulk-export all conversations into a local SQLite index for full-text and semantic search, and export media or Moments timelines as offline HTML. Everything runs locally and read-only on macOS, exposing 15 MCP tools plus a matching CLI.

Enables AI agents to connect to security cameras, detect objects with YOLOv8, recognize known faces, monitor restricted intrusion zones, capture annotated snapshots, and query a persistent SQLite event history.

Enables LLM clients to explore and query a local SQLite database through read-only, typed tools for table listing, schema inspection, ad-hoc SQL, customer lookup, and sales summaries.

Enables Claude to list Iceberg tables and run read-only DuckDB SQL queries, including time travel by snapshot, with per-caller token authentication and audit logging.

Shared, versioned tables with units, links and SQL. Agents read what your data means.

PostgreSQL, MySQL, and SQL Server in one session. 26 read-only MCP tools for AI agents.