"Eight" matching MCP servers:

Enables AI agents to maintain a small, curated set of durable personal memories in local Markdown via eight explicit MCP tools, avoiding unselective recall and temporary state.

Sovereign, encrypted, persistent memory for AI agents. Eight MCP tools — remember, recall, forget (GDPR Art. 17 erasure), share, governance. Anchored on COTI V2 mainnet. Apache-2.0.

Provides persistent, searchable memory for AI agents across any MCP-compatible client, storing project context, user preferences, and session learnings locally in SQLite with tools to save, retrieve, search, and manage them.

A design knowledge MCP server that Claude can query when generating UI, covering eight layers: principles, patterns, content design systems, research methods, service design, brand/visual, business strategy, and design tokens.

Enables read-only cognitive retrospect over Obsidian notes, surfacing stance changes, verifying claims with citable evidence, and avoiding unfounded causal stories via hybrid retrieval and eight read-only MCP tools.

Enables AI agents to capture, search, and manage structured memory from agent sessions with append-only events and provenance tracking, providing eight local MCP stdio tools.

Enables AI agents to query a curated, cited knowledge graph on testing, benchmarking, and auditing autonomous agents, returning claims with sources, confidence values, and evidence tiers through eight read-only tools over a remote streamable-HTTP endpoint with no authentication required.

MCP server exposing eight esoteric calculation systems (Western/Vedic astrology, Human Design, Gene Keys, and more) through 14 tools, with deterministic profiles, partial success, and OAuth integration.

An MCP server that stages Angel vs Devil inner conflict debates with deterministic relationship, memory, and turn management, letting client LLMs perform the dialogue.

scratchpad-mcp is an MCP server that gives AI agents persistent, token-efficient storage. Eight tools versioned file writes, structured line-diffs since a prior version, append-only logs with cursor pagination, on-demand summaries with per-version caching, and per-agent quotas. The point is to stop agents from re-reading files they've already seen and re-summarizing documents.

Local-first persistent memory for coding agents and MCP clients. It keeps important project context across sessions and reduces wasted tokens by retrieving only relevant memories instead of replaying unnecessary history.

Agentic PDF search via MCP, enabling intelligent document retrieval through LLM reasoning instead of vector similarity.

Transforms AI coding assistants into context-aware developers by auto-detecting project context, remembering conversations, and executing commands safely with a multi-layer security model.