"database" matching MCP servers:

Free, deterministic, theory-traceable computational-creativity framework that generates, develops, contrasts, evaluates, and synthesizes structured creative ideas through MCP, with no accounts, database, or model inference.

Hand a human a rich interactive UI by URL from any MCP client and get structured data back: forms, approvals, surveys, pickers, editable lists. Round-trip human-in-the-loop for agents.

Coordination for parallel coding agents: TTL file claims stored in the git common dir (visible across all worktrees), enforcement hooks that block colliding edits, agent presence, handoff notes, and a git-committed lessons knowledge base with BM25 search. Single static Go binary — no server, no database.

An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.

A provably read-only SQL layer for AI agents (MCP) and weekly reports — over the database behind an ERP (Logo Tiger, Netsis, Mikro). Statement-checking guard, measured against 28 attacks.

A plug-and-play MCP memory server with pluggable database backends that gives AI coding agents a persistent, shared knowledge graph for teams.

An advanced MCP server that enables Claude Desktop to act as an autonomous Oracle Database Administrator and Data Analyst with agentic schema discovery and self-healing queries.

A Model Context Protocol server providing LLMs with access to the Ensembl genomics database, enabling AI assistants to query gene information, sequences, variants, and other genomic data across multiple species.

Provides local, explicitly scoped memory for coding agents via MCP, storing durable project knowledge in a per-repository SQLite database with tools to record, search, and retrieve context.

A specialized toolchain that guides AI agents through a structured 'Atomic Development' workflow for building Python FastAPI and Supabase backends. It manages project scaffolding and enforces dependency-ordered generation of database models, API routes, and tests.

An MCP server that exposes structured Functional Requirements Documents (FRDs) to enable AI assistants like GitHub Copilot to automatically generate complete NestJS boilerplate architectures. It orchestrates the multi-phase creation of production-ready APIs including core CRUD, database integration, JWT authentication, and unit testing.

Enables coordinating multiple AI coding sessions by tracking features, decisions, and approval gates in a per-project Postgres database, with atomic IDs and commit-stamped append-only history.

Enables AI-assisted reverse engineering in IDA Pro by providing tools to analyze binaries, decompile functions, manage comments, search patterns, and interact with the IDA database through natural language.

BlueMouse is the "Prefrontal Cortex" for LLMs. It uses a 180k+ failure pattern database to validate code logic before execution, acting as a rigorous Quality Gate to prevent hallucinations and unsafe operations.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

Provides MCP tools that give AI agents persistent, append-only memory in a git repository, letting them record observations, decisions, and corrections while retrieving context briefs, current facts, conflicts, and traceable event history without a vector database.

Provides AI coding assistants with persistent project memory to retain architectural decisions, code patterns, and domain knowledge across sessions. It stores data locally in a SQLite database, allowing agents to remember, recall, and manage project-specific context using full-text search.

Provides persistent memory capabilities through Neo4j graph database integration, allowing storage and retrieval of interconnected knowledge with complex relationships between entities. Enables long-term retention and querying of information across multiple conversations through graph-based memory management.

Enables Claude to request and receive skills from a database on demand, allowing agents to fetch step-by-step instructions for tasks like lead research while keeping user credentials and execution on the user's own machine.

Enables AI agents and software engineers to investigate and resolve realistic distributed-system incidents using safe MCP-based diagnostic tools for code, logs, metrics, traces, database, and deployments.