"Information about Meta ads or advertising on Meta platforms" matching MCP servers:

Enables personal AI agents to combine Meta Ray-Ban audio/vision sensory grounding with long-term episodic life memory graphs and empathetic emotional resonance. Integrates with MCP-compliant clients via JSON-RPC stdio for ambient, context-aware interactions.

Enables personal AI agents to integrate multimodal Meta Ray-Ban audio and vision grounding with long-term episodic life memory graphs and empathetic emotional resonance. Supports proactive, context-aware assistance through sensory inputs, ambient telemetry, and task goals.

Enables AI agents to combine ambient multimodal perception, continuous episodic memory, and recency-decay context briefing for fast deterministic decisions and safe tool routing. It integrates with MCP clients to reduce unnecessary frontier LLM calls while enforcing token budgets and local-first memory retention.

Enables personal AI agents to fuse ambient multimodal perception with continuous episodic memory streams, routing routine reflexive actions at low latency while reserving heavier reasoning for ambiguous plans. Memory records apply Ebbinghaus recency decay with contradiction resolution and user-controlled deletion.

MCP server for the Meta-Consciousness (MCAI) theory: term definitions, concept relations and source citations, served from a local knowledge base.

Enables comprehensive management of Google Ads accounts by allowing users to create campaigns, manage keywords, and generate performance reports through a context-aware interface. It features a three-layer architecture that integrates product knowledge and historical campaign data to support intelligent decision-making.

On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.

Provides persistent, causal memory for AI agents with semantic recall, causal tracking, and importance-based forgetting through MCP tools.

Provides 78 tools for AGI experiments based on universal physics principles like entropy and criticality. It enables advanced long-term memory management, diversity-focused information retrieval, and meta-cognitive monitoring for self-improving AI systems.

A Meta MCP Server that provides persistent memory and intelligent guidance for MCP development projects.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

Enables AI assistants to manage memories via the mem9 memory service, supporting memory storage, semantic search, retrieval, update, and deletion across multiple platforms.

AutoMem MCP provides persistent memory for AI assistants, enabling them to recall information across conversations and platforms with graph-vector retrieval.

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

Your AI forgets everything between sessions. Rekindle fixes that. For Claude Code users who lose time re-explaining project context every session.

Exposes tools to ingest FigJam boards, retrieve context summaries, and answer free-form questions about the board content.

A local MCP server that maintains a persona profile (contact library) for AI assistants, allowing them to create, search, retrieve, supplement, and correct information about people mentioned in conversations via tools like search_profiles, get_profile, create_profile, update_profile, add_facts, update_fact, and delete_fact.

Agent memory for facts that change. When a user corrects something, Recall replaces the old fact, tells the agent what it replaced, and keeps the old value in a history. Ask what was believed on any date, see every change to a fact, or diff two dates. Runs locally on polign_db, Postgres with pgvector, MongoDB, or Qdrant. Apache 2.0.

A personal memory MCP server that ingests AI agent conversation logs from multiple platforms into a searchable PostgreSQL+pgvector database, enabling cross-session recall of past reasoning and decisions.

A personal knowledge hub MCP server that enables LLMs to query structured information about Akib Dabgar's skills, experience, projects, and goals using Dynamic Context Retrieval for efficient context usage.

Enables MCP-compatible agents to answer questions about you by exposing your CV through a tool, resource, and prompt.

MCP server for the Graphite Financial Knowledge Graph, enabling natural language queries about companies, supply chains, executives, regulations, and patents via MCP-compatible clients.

Gives AI coding agents persistent, evolving knowledge about a codebase, enabling them to store and retrieve observations about architecture, conventions, gotchas, and recent work context.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.

Enables complex problem-solving through multi-modal reasoning, dynamic knowledge graphs, meta-cognitive reflection, and collaborative AI personas.

Local MCP server that turns Mark Builds Brands' YouTube knowledge into an AI coaching assistant for ecommerce and Facebook Ads.

Enables Claude to query user-curated, dated memory entries stored locally, giving users direct control over what the AI remembers about them.

Enables AI agents to semantically search, ask questions about, and analyze videos, with persistent memory and social media import capabilities.

Connects AI assistants like Cursor and Claude to your local Daylens timeline so they can answer questions about your past work sessions, no cloud or API keys needed.

Local-first, code-aware engineering cognition for AI coding agents - persistent memory, contextual retrieval, and continuous cognition about your codebase.