"LibreOffice office suite software" matching MCP servers:

MCP server for tracking decision logs and open questions in AI-assisted projects, offering tools to fetch context, list decisions and open items, and draft new decisions.

Enables interaction with Google NotebookLM through a unified CLI and MCP server, featuring automatic multi-browser authentication and support for notebook queries, source management, notes, and audio generation.

Provides MCP tools for workspace initialization, health checks, context recall, and durable memory capture, enabling project-specific memory and shared company knowledge with citations.

Enables evidence-first, tenant-isolated knowledge management and business-scenario execution for Accio Work foreign trade, with honest unavailable responses when connectors or approvals are missing.

A set of four local MCP servers that help solo developers maintain context across sessions by providing searchable memory, session journals, file checkpoints, and project overviews. All servers run locally with minimal dependencies and work with any MCP-capable client.

MCP server providing permanent, intelligent memory for AI coding assistants with retrieval, Hebbian learning, and governance, plus personal memory modules for accounts, habits, experiences, knowledge, and lifestyle. Enables AI assistants to recall project context across sessions and manage personal data securely.

A git-backed MCP server that centrally manages AI agent skills, tools, and knowledge with role-based access, change requests, and a remote OAuth 2.1 endpoint.

Local markdown notes for any MCP client: ranked + semantic search, tags, todos, a wiki-link knowledge graph, daily notes, templates, and slash-command workflows. Pure-JS, local, no API keys.

Provides read-only access to the Family Office Knowledge Graph, enabling resolution of family offices, retrieval of public records with provenance, and listing of events, aliases, and nodes.

MCP bridge for PDF Content Search — full-text PDF search with Apple Vision OCR across thousands of documents in under a second from Claude, Cursor, or any MCP client. Advanced filters (date, category, sender, amount), wildcards, boolean operators. Bridge open-source (MIT), PDF Content Search app is commercial with free iOS+Android companion scanner apps.

The coordination layer for AI agent networks, providing persistent memory, task management, inter-agent messaging, and human oversight through native MCP tools.

Universal MCP knowledge server for LLM agents, powered by local RAG, providing domain-specific best practices and playbooks across software engineering, marketing, video editing, and other knowledge areas.

A local-first MCP server that gives AI coding assistants persistent, structured, human-readable memory for a software project by storing project knowledge as Markdown files in the project's .dev-context-memory/ folder.

Public, agent-searchable knowledge base about AI-native software development, served as an MCP server with tools to search, read, and list topics.

Exposes the MITRE ATT\&CK framework to LLMs and AI assistants via the Model Context Protocol, enabling querying of techniques, tactics, groups, software, and mitigations.

Automatically generates and manages a prompts system for software projects, enabling persistent context for AI coding assistants through project scanning, requirement clarification, and module tracking.

Enables storing and querying structured information about software code entities (classes, functions, files) and their relationships (calls, imports) along with qualitative observations like design decisions and change rationale.

Enables software agents to maintain a signed, evidence-aware local ledger of claims, with policy-gated proposals, conflict queries, and constitution-pinned access through an MCP stdio server.

An all-in-one MCP server that enables AI agents with local system capabilities like filesystem navigation, command execution, desktop automation, and a continuity memory suite for persistent cross-session project context.

Persistent visual cache for LLM-driven software development. Caches screenshots using perceptual hashing, vector search, and AX trees to prevent token overhead and visual hallucination loops.