"Restaurants with good Google Maps reviews" matching MCP servers:

MCP server that retrieves up-to-date Google Maps Platform documentation and code samples to ground AI-generated code in official guidance.

Enables AI assistants to read and analyze Google Docs comments, including authors, status, quoted text, and reply threads, via a read-only interface with OAuth 2.0 sign-in.

Provides AI-powered search and documentation tools using Google Vertex AI or Gemini API with real-time web search grounding, enabling technical queries, code analysis, documentation retrieval, and architecture recommendations to overcome LLM knowledge gaps.

Enables MCP clients to search, read, list, create, update, and delete Wiki.js pages using a user's own Google Workspace identity, with Wiki.js enforcing all authorization.

Fetches the complete record of a single patent by publication number — full claims, paged description text, CPC classifications, worldwide family with legal status, backward/forward citations, legal events and prosecution timeline — rendered as compact Markdown for an LLM. It does not search, and is meant to be paired with a keyword search server to go from candidate publication numbers to full patent details.

MCP server that reads Google Docs and Google Sheets content for AI assistants like Claude.

Enables reading, editing, suggesting, and commenting on Google Docs from any MCP client, with scoped reads, minimal-diff edits, and support for tables, tabs, and layout.

About MCP server for Google Agent Platform Docs — Google AI + Vertex AI. 3400+ pages searchable by AI agents.

Enables LLMs and AI agents to query Google Ads accounts, inspect resource metadata, list accessible customers, and retrieve reporting metrics, segments, discovery documents, and release notes via the Google Ads API.

Enables hybrid search (BM25 + semantic with RRF) over documentation, with Thai language support. It exposes MCP tools for adding documents and searching via Qdrant and Ollama/OpenAI, using a stateless Streamable HTTP transport.

Enables AI assistants to search and access Google Cloud Platform documentation in real-time, supporting 20+ GCP services with natural language queries and smart content extraction.

Enables unauthenticated MCP access to Google Cloud documentation by proxying requests to the Developer Knowledge API, allowing coding agents to query docs without direct Google authentication.

Enables AI assistants to search and access academic papers from Google Scholar via MCP protocol, with support for keyword, author, and year filtering, CAPTCHA handling, and BibTeX retrieval.

Connects Claude to Google Docs, allowing users to list, read, create, update, search, and delete documents in their Google Drive through natural language interactions.

A local stdio MCP bridge that forwards tool calls to the Google Developer Knowledge MCP endpoint and enhances search_documents with caching, result expansion, and concise markdown excerpts.

Enables reading and searching API documentation from YApi instances, allowing AI models to access interface definitions, project API lists, and search through API endpoints using YApi URLs or project IDs.

An MCP (Model Context Protocol) server that turns the book Deep Learning with Python (François Chollet) into a searchable knowledge base, so Claude can act as a deep-learning/ML expert grounded in the book's content.

Enables Claude to read and analyze PDF documents with automatic OCR processing for scanned files. Features intelligent text extraction, caching for performance, and secure file access with search capabilities.

Deterministic navigation maps over code AND markdown for AI agents: one MCP server, two lenses (tree-sitter TS/JS/Python + markdown). Map a whole project, read one function or one doc-section, ~99% less context. Merges codelens + docslens.

MCP server that lets AI agents read and search project documents in OMOS Shared Drive, with source-referenced answers and Google Drive links.