"SQLite" matching MCP servers:

Enables AI agents to query and explore SQLite databases through schema inspection, arbitrary SQL execution, and predefined canned queries. Compatible with Datasette metadata for enriching database structure with descriptions.

Offline RAG MCP server that indexes documents into SQLite with hybrid vector and lexical search, and enables natural language queries via Claude.

Enables MCP clients such as Claude Desktop, Cursor, Zed, and Windsurf to recall associative context from a folder of markdown notes, combining vector search entry points with one-hop [[wikilink]] graph expansion and cross-encoder reranking over a single SQLite file. It also appends a zero-token per-turn ledger of asks, files, tools, and decisions that agents can consult across sessions.

A Python-based SQLite MCP server supporting database read/write operations with natural language interaction capabilities, packaged for Docker deployment in stdio mode.

A server that exposes SQLite database operations as tools, allowing natural language interactions with a database through LlamaIndex and Ollama LLM integration.

Enables AI agents to store, search, update, and manage local long-term memories with namespaces, tags, expiration, and audit trails, without requiring cloud accounts, API keys, or network access.

A Model Context Protocol (MCP) server implementation that provides database interaction and business intelligence capabilities through SQLite. This server enables running SQL queries, analyzing business data, and automatically generating business insight memos.

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.

Query SQL databases (SQLite, PostgreSQL, BigQuery, Databricks) in natural language through a business semantic layer — glossary, metrics, and a data dictionary grounded against your real schema. Read-only by default, with an embedded SQLite + sqlite-vec metadata store and no external infra required.

Local-first MCP memory server that gives AI coding agents long-term memory via SQLite and sqlite-vec, with optional LLM-powered layering. No gateway or API key required.

Local code context engine for Codex App/CLI that indexes code with SQLite/sqlite-vec for hybrid search and context packing to provide relevant files, line numbers, snippets, and paths.

Cross-client AI memory hub for AI agents. Lets Claude Code, Cursor, Windsurf, and 20+ other clients share one physical SQLite memory database. Features bi-temporal time axes, source attribution, Q-Value usage-based ranking, and FTS5 full-text search with SQLite triggers.

Enables Claude to query and manage databases (SQLite, SQL Server, PostgreSQL, MySQL) through natural language, supporting read/write operations and schema management.

Local-first MCP server for querying multi-repo engineering documentation artifacts from a SQLite corpus.

Long-term memory MCP server for Claude Code with SQLite persistence, encryption, semantic search, and automatic memory linking.

Provides persistent local memory for AI assistants using SQLite and semantic search, enabling context-aware conversations.

A flexible Model Context Protocol server that enables LLMs to interact with database systems, supporting dynamic schema discovery and query execution across PostgreSQL and SQLite backends.

Answers queries based on Alex Hormozi's YouTube content using local RAG with SQLite and vector embeddings.

Retrieves indexed Confluence pages via semantic search, returning chunks, citations, and page bundles; stores embeddings in local SQLite with sqlite-vec.

MCP server enabling natural-language querying of SQLite databases via schema discovery, GraphRAG retrieval, and safely guarded read-only SQL execution.