"Understanding and Using Analytics Tools" matching MCP servers:

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

Extends VS Code Copilot with MCP tools for persistent semantic memory, code indexing and RAG search, sandboxed Python/shell execution, web fetch/search, dynamic tool management via a web UI, and structured multi-step reasoning.

Enables natural language interaction with Obsidian vaults through an MCP server, providing hybrid search, file management, and AI-powered analysis.

Provides MSP support tools (ticket search, draft response, KB search, update) with a deterministic security guardrail that refuses to draft responses for security tickets based on content scanning, even if mislabeled.

A MongoDB Atlas-based Notion-style knowledge base management MCP server that supports user workspaces, project management, page CRUD with tree structure, and text search.

Enables searching, reading, and appending change notes in an Obsidian vault through local MCP tools.

Enables semantic search across Apple Mail, Messages, Calendar, and Contacts on macOS using natural language queries. All processing happens locally with privacy-first vector indexing for fast similarity search.

A collection of MCP servers for Apple macOS apps (Mail, Contacts, Notes, Memory, Messages, Calendar, Reminders) enabling AI assistants to read, search, create, and update data via JXA, SQLite, and EventKit.

A Model Context Protocol server that provides AI assistants with structured access to your Logseq knowledge graph, enabling retrieval, searching, analysis, and creation of content within your personal knowledge base.

A Model Context Protocol server that enables AI agents to interact with a local Logseq instance, allowing operations like creating pages, managing blocks, and searching across a knowledge graph.

A Model Context Protocol server that enables AI agents to interact with local Logseq knowledge graphs, supporting operations like creating/editing pages and blocks, searching content, and managing journal entries.

Enables local semantic search and management of OKF knowledge bundles via MCP tools, with hybrid BM25 and vector search.

Persistent memory layer for MCP-compatible AI agents. Implements save/recall/search over a local SQLite session store via 14 MCP tools. Auto-loads relevant context at session start. No cloud dependency. Works with Claude, Cursor, Codex, Hermes Agent. Free (50 sessions) / Pro ($8/mo).

Versioned document vault system for MCP-compatible AI agents. Organizes reference knowledge (specs, contracts, rules) into per-project vaults with 36 MCP tools for inject, search, link, and version operations. Local SQLite backend. Works with Claude, Cursor, Codex, Hermes Agent. Free (3 vaults) / Pro ($9/mo).

Provides context management and todo persistence with AI second opinions from ChatGPT and Claude. Enables saving code snippets, conversations, and todos across sessions with full-text search capabilities.

Provides AI agents with tools to navigate, search, and manage a hierarchical knowledge base of themes, skills, and learning resources with tenant-aware JWT authentication.

An enterprise-ready MCP server that provides persistent sentiment analytics, churn prediction, and automated risk alerting for customer conversations. Enables Claude to track sentiment trends, detect at-risk customers, generate reports, and maintain historical context across interactions.

Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.

Enables Claude and ChatGPT to share a single study-progress database for interview prep, coursework, and spaced repetition, with per-user data isolation and server-side SM-2 scheduling for due reviews and study plans.