"An agent for accessing marketing data and brand assets to grow a company" matching MCP servers:

Secure, local-first collaboration layer for AI agent teams, enabling authenticated agent-to-agent communication, shared memory with provenance, and scoped service execution through MCP.

Enables AI agents to query and manage company knowledge from a Supabase GraphRAG store, including accounts, meetings, people, org hierarchy, product docs, and call logs.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

An MCP server that acts as an AI knowledge and skills hub, automatically discovering, indexing, and serving skill libraries to any MCP client with full-text search, rich metadata, and hot reload.

An MCP server that provides shared memory, kanban board, and agent registry for AI agents to collaborate as a team, with a live dashboard for human oversight.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

Enables semantic search over the CCI Black Book, a scanned grow manual, retrieving both text and visual content with cited evidence packs for AI assistants.

A robust MCP server that transforms OneNote notebooks into an AI-accessible knowledge base for Gemini Spark, enabling natural language queries to list, read, and search notes via Microsoft Graph API.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Persists Claude Code sessions to Notion as team memory, enabling queryable recall of decisions, work state, and project architecture.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Local, searchable project memory for AI coding agents. Markdown source of truth, MCP interface, safe structured updates

A self-improving knowledge agent that provides local retrieval, web research, and structured answer synthesis for Claude Code and VS Code Copilot via MCP. It enables AI tools to manage a project-specific knowledge lifecycle through automated research and indexing.

An MCP server that enables AI agents to compile, refine, and interlink knowledge into a persistent wiki, replacing RAG with structured, curated knowledge.

MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others. The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.

Provides a single-writer MCP server for a governance-grade knowledge base of markdown documents with version control and query capabilities.

A provider-neutral MCP server that provides tools for managing skills, agents, references, and artifact memory in a local workspace.

Local-first memory engine for AI-agent teams: private/team/project ACL, associative recall, and federated sync across nodes. One SQLite file, no LLM required.

An MCP server that gives multiple agents a shared versioned memory with explicit handoff packets, enabling structured context transfer and stale data detection across sessions.