"Memory and Database Solutions for AI Systems" matching MCP servers:

An MCP server that exposes a curated database of generative AI tools as four tools an AI assistant can query directly, enabling searches without relying on model knowledge.

Provides comprehensive GDPR compliance assessment tools for AI/ML systems, including lawful basis determination, DPIA generation, and data subject rights handling. It also crosswalks GDPR requirements to EU AI Act obligations with AI-specific considerations throughout.

Enables AI-powered access to authoritative design systems knowledge, including W3C standards, WCAG guidelines, and best practices from 188+ curated entries via semantic vector search.

MCP server for step-by-step mathematical reasoning and planning, enabling AI agents to execute calculations and perform GUI actions like opening PowerPoint.

Automatically discovers database schema, performs data quality checks on tables and columns, and generates natural-language root cause analysis reports using Ollama LLM.

Enables MCP-capable AI clients to read and write structured, project-scoped memory through a Cloudflare Worker backed by D1 and R2.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

Provides persistent long-term memory for AI agents with semantic search and activation-based decay. Enables AI systems to remember across sessions through layered memory architecture and automatic context-aware retrieval.

Smart memory for AI agents. Solves the Karpathy problem: memories decay, topics are frequency-weighted, one-time questions don't become obsessions. 7 tools. Zero deps.

Provides persistent memory for AI assistants via MCP, enabling them to store and recall facts, preferences, and tasks across conversations using either local file storage or a cloud backend with semantic search.

Enables AI assistants across Claude Code, Claude Desktop, Codex CLI, and Gemini CLI to remember and automatically apply user-confirmed behavioral instruction presets, with a trust curve for scheduled re-confirmation and one-command uninstall.

Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.

Persistent memory MCP server for AI agents, using SQLite with hybrid keyword and semantic search for long-term memory storage.

Cognitive memory engine for AI agents with 5,100+ knowledge modules, circadian rhythm awareness, emotional state tracking (PAD model), and hybrid semantic search. Supports persistent per-user memory, project-scoped contexts, and multi-protocol access.

Provides AI agents with associative long-term memory using Sparse Distributed Memory, enabling recall from vague cues and interference detection.

An MCP server that integrates with fal.ai to provide AI agents with tools for image generation, text processing, audio synthesis, and model management via a unified interface.

A fully local persistent memory layer for LLM coding agents (Claude Code, Codex, Gemini CLI, OpenCode). A shell wrapper intercepts tool invocations, fires hooks on every tool call, then runs a 3-layer pipeline (extract → compress to ≤500-token digest → merge into project memory doc) at session end. The next session gets prior context injected automatically.

Persistent project memory for AI models and coding agents. Memory MCP stores architecture, decisions, tasks, warnings, preferences, and session state in Supabase so OpenCode, Claude Code CLI, Qwen Code, Codex, or any MCP-compatible client can resume work without losing context.

Provides AI coding agents with a local knowledge-graph memory, enabling cross-project retrieval via PageRank diffusion and tools to retrieve, write, extract, update, and view recent knowledge over MCP.

Open-source AI memory layer for LLM agents. Importance scoring, temporal decay, hierarchical memory (facts, summaries, themes), YMYL prioritization, and active retrieval with contradiction detection. Supports OpenAI, Anthropic, Ollama. Local-first with SQLite + FAISS.