"Zaim" matching MCP servers:

Enables AI agents to inspect verified multi-cloud architectures, certifications, runbooks, and projected FinOps cost savings, and to submit encrypted consultation inquiries through MCP.

MCP server that provides web search functionality using the Tavily API. It runs in stdio transport mode and can be integrated with Cursor or other MCP clients.

MCP server for Yandex Direct, Metrika, Search API, Wordstat and Webmaster. Connect an AI assistant to advertising, website analytics, search results and search-demand data.

Enables searching and reading the public AI Mastermind LT community archive, including full-text search, message retrieval, and access to shared links and files, through natural language queries.

Provides web search, content extraction, and AI summarization capabilities using the GLM-4.7-Flash model. It enables users to perform web searches, fetch website data, and generate concise content summaries through integrated tools.

Enables large language models to directly access and search content in ZIM files, allowing offline question answering and information retrieval from resources like Wikipedia.

Market knowledge layer for AI agents. Aim monitors millions of sources — news, podcasts, social, competitor moves and regulatory filings — and surfaces the signal shaping your market. Hosted remote MCP server (streamable HTTP, OAuth).

Enables offline CRUD and semantic search on Wikipedia ZIM archives via MCP tools for reading, writing, editing, deleting, and searching articles.

MCP server that exposes SQLite datasets as queryable tools and resources via Streamable HTTP, enabling read-only exploration and SQL queries.

Enables interaction with .zim archives by providing tools for article search, content retrieval, and metadata discovery. It features a TF-IDF based RAG engine for semantic retrieval over extracted article chunks from compressed ZIM files.

Enables reading and searching ZIM files for offline reference content like Wikipedia.

Enables managing Topvisor projects and keyword lists, organizing keywords, configuring search regions, and reading saved ranking history.

Enables AI assistants to query a person's CV and portfolio content via MCP tools and resources, returning grounded answers from local markdown data instead of relying on resume parsing.