"Information about Advertising" matching MCP servers:

Enables AI assistants to search and ask questions about documents stored in AnythingLLM workspaces through MCP tools.

Enables AI assistants to search and retrieve transcripts from the Entra.Chat podcast about Microsoft Entra ID, with timestamped YouTube links and guest information.

Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.

A Model Context Protocol server that allows AI agents to perform WHOIS lookups, enabling users to directly ask the AI about domain availability, ownership, registration details, and other domain information.

Provides LLMs with specialized knowledge about fountain pen inks, enabling intelligent ink search, color matching, and recommendations through various tools.

A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.

Provides personalized Data Engineering learning updates by fetching recent news about DE concepts, patterns, and technologies, while tracking user knowledge to present only new information relevant to their learning journey.

A server that connects MCP clients (Claude, Cursor, Windsurf, etc.) to EventCatalog instances, allowing users to ask questions about their event-driven architecture and get insights about domains, services, and message schemas directly within their development tools.

A Model Context Protocol server that provides natural language access to Cortex API, enabling users to query information about their system's structure and make faster decisions about services, incidents, and team responsibilities.

Enables AI agents to query up-to-date, sourced information about workflow automation services, AI agents, integrations, pricing, case studies, FAQs, and contact details in Dutch and English through read-only tools.

Exposes a personalized AI agent that reads your resume and provides intelligent responses about your professional background through a standardized MCP server interface with RAG capabilities.

MCP Memory is an MCP Server that gives MCP Clients the ability to remember information about users across conversations. It uses vector search technology to find relevant memories based on meaning, not just keywords.

MCP server for local-first RAG over Obsidian vaults, enabling AI agents to search and ask questions about notes with grounded citations.

CTX is a tool made to solve a big problem when chatting with LLMs like ChatGPT or Claude: giving them enough context about your project.

Enables users to query information about LPDP scholarship financial disbursement using RAG with Pinecone vector search and Gemini 2.0 Flash, answering questions about funding components, deadlines, living allowances, and required documents.

A Model Context Protocol (MCP) server that enables LLMs to interact directly the documents that they have on-disk through agentic RAG and hybrid search in LanceDB. Ask LLMs questions about the dataset as a whole or about specific documents.

An MCP server that provides deep knowledge about OpenAI APIs and SDKs, enabling users to query technical information through various MCP clients including ChatGPT Deep Research, Cursor, and OpenAI Responses API.

A persistent memory system using a local knowledge graph that enables Claude to remember information about users across chats, with advanced search, graph traversal, and filtering capabilities for entities, relations, and observations.

Enables local-first, source-cited AI answers about your TTRPG campaign lore from your own documents, usable in Discord, Foundry VTT, or any MCP client while refusing to invent information outside your sources.

A local-first iMessage retrieval system that serves hybrid full-text and vector search over an MCP server, enabling an AI assistant to answer questions about your correspondence.

Enables querying a Neo4j knowledge graph about Wroclaw University of Science and Technology using natural language. Converts user questions into Cypher queries and retrieves contextual information through an intelligent RAG pipeline with LLM-powered query routing.

Enables AI assistants to answer questions about the operator's current focus, engagements, reusable patterns, availability, and service offerings, with responses grounded in structured data and including confidence labels and source citations.

An MCP server that provides country-related data from the REST Countries API, allowing users to query information about countries through natural language.

A tool that connects Google Ads with Claude AI, allowing users to analyze advertising data through natural language conversations and access campaign information, performance metrics, keyword analytics, and ad management.

Enables MCP clients to quickly extract information about GitHub repositories, including repository summaries, project directory structures, and file contents.

Enables MCP clients to search and ask questions about Arknights world lore through hybrid retrieval and retrieval-augmented generation, with source annotations on generated answers.

Enables users to ask questions in Portuguese about marketing metrics (ROI, CAC, LTV, pipeline, channel attribution) by querying a marketing data warehouse through MCP tools.

Automatically routes natural language questions to RAG or Text2SQL paths to answer queries about virtual construction site data, supporting semantic search and structured aggregation.

Provides MCP tools for searching, retrieving, and answering questions about indexed Nextcloud developer documentation from multiple sources.

Grounds AI answers about a business in real, verified data sourced live when needed or cached for reliability, preventing hallucinations.

Enables AI assistants to query a corpus of job offers via natural language, using BM25 search, facets, and trend analysis to answer questions about skills, positions, and timelines.

Translates plain English questions about infrastructure operations into SQL queries, executes them against a database, and returns the real answer.

Enables external clients to query a vector knowledge base about skills and roles through an MCP retrieval tool, supporting RAG-based question answering with tool-calling.

Minimal MCP server exposing the Onli Knowledge Base, enabling retrieval of factual information about the Onli ecosystem via API requests.

An MCP server that provides information about IIT Guwahati campus life using a RAG pipeline backed by Qdrant Cloud.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

Local MCP server that provides verified answers about Jimmer and internal libraries using a SQLite FTS5 knowledge base.

Enables AI assistants to answer questions about French administrative procedures for individuals, professionals and the self-employed using only official service-public.gouv.fr guides. Every answer returns verbatim official text with a citable link and last update date, and flags low-confidence results when nothing relevant is found.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

MCP server for searching French and European law, providing natural language access to jurisprudence, consolidated legal texts, and related legal information via tools like search_decisions and search_legal_texts.