"facebook ads" matching MCP servers:

Enables users to access, search, and get recommendations from AWS documentation through natural language queries. Supports both global AWS documentation and AWS China documentation with tools to fetch pages, search content, and discover related resources.

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

Enables LLMs to run complex graph algorithms on Neo4j databases, answering graph-related questions by selecting and executing appropriate parameterised graph algorithms.

MCP server providing persistent memory for LLMs via semantic search over captures, structured facts with temporal tracking, and document ingestion. Enables any MCP-compatible client to maintain a searchable knowledge base across sessions.

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.

Self-hosted memo knowledge base with MCP, REST, and read-only web interfaces; lets AI agents save and retrieve tagged, searchable study notes for AWS DevOps Pro exam prep.

Exact recall from a plain-text index you keep: recall, find, tags, timeline over stdio. Read-only by default; ais --mcp rw adds saving; no delete at any setting. Encrypted values stay opaque to the agent

A high-performance MCP server providing long-term memory storage with semantic and keyword search capabilities, using SQLite and fastembed for sub-200ms queries.

Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.

A high-performance MCP server providing long-term memory storage with semantic and keyword search, along with a structured agenda engine for task management.

MCP server that gives AI agents persistent, tenant-scoped memory with semantic search and consolidation, using CockroachDB vector indexes and Amazon Bedrock embeddings.

Refines development prompts and stores semantic memory to save tokens in complex Antigravity tasks, enabling token savings and enriched context.

This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.

Enables coding agents to record, search, and supersede ADR-style decisions and machine-checkable constraints stored as git-friendly markdown in a repository, linked to SpecGate requirement ids, tests and commits. It also surfaces the relevant constraints and decisions for a task and checks a proposed change or diff for conflicts before it is committed.

Enables local, offline querying of birthdays and biographical tags for celebrities, historical figures, and ACG characters, including date-based lists, name/alias search, person details, and upcoming birthdays.

Enables searching imported AI conversations locally across different providers from an MCP client, with read-only access to the archive.

Enables humans and AI agents to collaborate live on documents in a browser-based editor, with agents connecting via OAuth-enabled MCP tools for writing, commenting, memory, files, web retrieval, and backups. It can optionally integrate school drive and learning-platform access.

Enables Claude to intelligently query and analyze your resume using RAG technology. Supports skill matching against job requirements and answering questions about your professional background from locally stored resume files.

Enables users to create, retrieve, update, delete, and list notes through an MCP server, with persistent JSON storage and atomic writes.

Enables AI clients to incrementally build and maintain a git-backed personal wiki, providing long-term memory by compiling and cross-referencing knowledge across sessions.