"Information about SQLite database software" matching MCP servers:

Enables coding agents to query and modify a SQLite database through twelve SQL-based tools, with safety enforced server-side via statement policies, protected tables, result caps, and snapshots. It also provides an append-only, hash-chained memory log with checkpoints so agents can record events and resume context across sessions.

A zero-config MCP server that enables AI to access, analyze, and manage local SQLite databases with secure read-only querying and automatic schema discovery.

Enables MCP clients to add, search, and delete persistent namespace-scoped notes through a local stdio server backed by a SQLite database. Namespaces isolate queries and content-derived IDs make repeated writes idempotent.

Provides comprehensive SQLite database interaction for AI agents, including data manipulation, schema inspection, and automated query logging. It features a unique context preservation pattern that uses a dedicated meta-table to help autonomous agents maintain self-documenting database architectures.

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.

Governed cross-agent memory for coding agents with hybrid retrieval, provenance tracking, and cross-machine sync.

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

Fireproof ledger database with multi-user sync

Provides persistent memory, skill tracking, failure indexing, and context sharing for Claude Code using SQLite with FTS5 full-text search.

A graph-friendly relational server that stores project memory, tasks, and metadata in a centralized SQLite database as the authoritative source of truth. It enables AI agents to manage complex project states through entity-relationship modeling and can generate human-readable markdown views on demand.

Provides persistent memory and knowledge graph capabilities for AI assistants using local SQLite storage. Enables creating, searching, and managing entities, relationships, and observations with vector search support across conversations.

A personal knowledge graph and memory system for AI assistants using SQLite with FTS5 full-text search, enabling persistent memory across conversations with Claude or any MCP-compatible AI.

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.

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.

Provides a dynamic SQLite-backed code knowledge graph for AI assistants, with MCP tools to inspect symbols, find dependency paths, and analyze code structure across multiple languages.

An MCP server that provides deterministic math computation (numeric, symbolic, unit, matrix) and hybrid retrieval over study notes/textbooks with citations, helping Claude become a reliable study partner.

Enables LLM agents to maintain structured long-term memory and knowledge using SQLite, with graph storage and relational query tools for persistent context.

Self-documenting MCP server enabling AI agents to autonomously create, manage, and query SQLite databases with enforced metadata requirements for discoverability.

A git-backed MCP server that centrally manages AI agent skills, tools, and knowledge with role-based access, change requests, and a remote OAuth 2.1 endpoint.

Enterprise MCP server that exposes multiple MySQL databases to AI services through one endpoint, with API-key auth, per-key database scoping, a layered SQL guard, and a markdown schema-knowledge graph.