"Context Memory Systems and Techniques" matching MCP servers:

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

A stateless MCP server for composing, validating, auditing, and rendering consequential documents from a small semantic model.

Provides live web and document intelligence, including search, company news, scraping, crawling, structured extraction, document parsing, brand intelligence, screenshots, website monitoring, and batch jobs.

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.

Enables AI clients to read and write to a user-owned markdown bucket via S3-compatible storage, providing a persistent shared context layer across different AI tools.

An MCP server serving a curated corpus of thinking techniques for AI agents, with tools to classify intents, find and apply techniques, and verify their effectiveness.

Read-only MCP server for the July 2026 survey of AI in open-source design systems, enabling agents to query 19 systems' affordances, coercion techniques, and platform data via 9 tools, 2 resources, and 2 prompts.

Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.

MCP server providing deep PostgreSQL context to AI assistants, including schema DDL, index health, foreign key associations, query execution plans, and performance statistics via read-only tools.

Provides persistent context management for AI agents by storing and querying semantic information using Upstash Vector DB and Google AI embeddings. It enables semantic search, batch operations, and metadata filtering to help agents retrieve relevant stored knowledge.

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.

Persistent memory and handoff intelligence layer for MCP agents. Most memory servers retrieve text — Memory Nexus compounds operational context, learning from usage and progressively synthesizing observations into higher-order intelligence across sessions and tools.

A portable, user-owned memory for MCP-capable agents in VS Code, enabling cross-agent recall and memory creation.

Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents, giving them deep context from your entire codebase.

Shared, live team memory for Claude — a remote MCP server on Cloudflare Workers + D1.

Provides LLMs with persistent memory and reusable skills via MCP, enabling semantic storage and retrieval of user preferences, project context, and step-by-step procedures across conversations.

Enables personal memory management through tools to find people, get profiles, remember notes, and perform semantic search, integrated with Claude via SSE.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

Enables Claude to pull curated context from self-hosted Markdown files via a remote MCP connector, with an append-only journal for agent notes manually promoted by the owner.

An MCP server that stores project memory in Supabase, allowing AI tools to persist context, notes, and decisions across sessions. Enables Claude Code, Codex, and similar assistants to maintain long-term project continuity through persistent memory storage.