"SQLite" matching MCP servers:

Enables LLM assistants such as Claude Desktop and Cursor to discover database schemas and run strictly read-only SELECT/EXPLAIN queries against local database files. Includes parser- and engine-level blocking of mutations, result truncation to prevent context overflow, and structured error responses that help models self-correct.

MCP server for SQLite — query databases, inspect schemas, explain queries, and export data from your IDE.

Enables AI agents to safely work with SQLite databases by enforcing read/write separation, dry-run writes with confirmation, automatic backups, and an audit trail.

Simple, fast, long-term memory for your AI chatbots, agents, and MCP tools. Give your LLM a persistent memory using a local SQLite file. No complex database servers, no heavy cloud setup, and zero C++ compilation errors. Works everywhere.

Deterministic SQL static analysis and query-equivalence checking for Postgres, MySQL, SQLite, and SQL Server. Tokenizes locally before forwarding to the API.

Five-layer agent memory over MCP. zenbrain_store routes each memory: steps to a procedure, emotional weight to an episode, high confidence to a pinned core memory, the rest to a semantic fact. zenbrain_recall returns results with id and layer; zenbrain_forget deletes one plus what consolidation linked to it; zenbrain_consolidate runs one sleep-like pass. Local SQLite, no account, no network call.

Local long-term memory shared by every AI coding assistant on one machine: a single SQLite file with FTS5 search and optional multilingual semantic search, no daemon and no cloud.

Read-only-by-default MySQL/MariaDB, PostgreSQL and SQLite access for AI agents: explore schemas and foreign keys, search, sample, query and EXPLAIN with token-efficient TOON output. Writes only when enabled, always previewed and atomic.

Enables AI coding agents to retrieve relevant execution context before a task, compare candidate paths, log outcomes, and search past experiences stored locally in SQLite. It lets agents reuse what worked on similar tasks and get live alerts when a run stagnates or repeats failures.

Records your terminal sessions per command (PTY + OSC 133) into local SQLite, so AI agents can search, retrieve, and diff what commands actually printed. Secret redaction is applied by default to everything served over MCP.

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

Provides read-only access to Withings health metrics including body composition, sleep, workouts, and ECG data with local SQLite caching and trend analysis. Features incremental synchronization, automatic OAuth token refresh, and supports all 200+ Withings measurement types for comprehensive health tracking.

Provides AI coding tools with one local SQLite memory and rules store they can read over MCP, REST or the CLI, so facts, sessions and goals persist across sessions and shared rules are written into each tool's own instruction file. Runs entirely on your machine with no account, telemetry or network calls by default.

Enables AI assistants to maintain a persistent, local memory using SQLite with ranked full-text search, German morphological matching, and two-axis filing, all without external services.

Provides AI agents with a local, private Markdown-based memory vault and SQLite search. Enables agents to search, read, list, and traverse linked knowledge pages via MCP with zero external runtime dependencies.

Database MCP server for MySQL, MariaDB, PostgreSQL & SQLite

Provides local MCP tools to query your own Xiaomi Mi Fitness health data (sleep, workouts, heart rate, etc.) stored in a local SQLite database, enabling AI assistants to access personal health records without exposing credentials.

Hand a project over — to your next session, to Cursor/Codex/Gemini, to your successor — with the reasons attached. Local-first memory MCP for coding agents: decisions re-injected before the agent acts, drift detection across every project you run. One SQLite file, nothing leaves your machine.

Provides AI agents with version-pinned NVIDIA CUDA-Q documentation, API reference, and runnable examples via MCP, using offline SQLite full-text search. It resolves docs to match the installed cudaq package to avoid version skew.

Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.