"Google search or related query" matching MCP servers:

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.

Provides 14 enhanced intelligent search tools for both international platforms (GitHub, StackOverflow, NPM, etc.) and Chinese platforms (CSDN, Juejin, WeChat docs, etc.). Each tool includes smart URL generation, search tips, and related suggestions for comprehensive technical research.

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.

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

Enables AI assistants to load, parse, and query OpenAPI/Swagger documentation from URLs with intelligent search across endpoints, schemas, and authentication methods. Provides 10 specialized tools for comprehensive API exploration including path details, operation lookups, and multi-criteria search capabilities.

Enables coding agents to list, search, and read a curated Shopware developer and merchant knowledge base offline as plain Markdown files, without network access or an API key.

A read-only MCP server for ServiceNow that provides deep visibility across multiple instances via query, schema inspection, identity, workflow, and code search tools.

Search Vascue's public healthcare-operations documentation: AI front desk for clinics, provider-side insurance claims automation, Cliniko integration, security. Public content only.

Exposes an internal engineering knowledge base to AI assistants, allowing users to search and retrieve standards, runbooks, and architecture decisions. It supports RAG-enhanced search, document scraping, and specialized prompts for incident investigation and code reviews.

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.

MCP server for token-efficient access to Open Finance Brasil rules, enabling coding agents to search and retrieve specific regulations, OpenAPI specs, and business rules through progressive disclosure.

Lets AI agents search and read a folder of Markdown documentation at query time, exposing heading-level search, whole-page or section retrieval, and page listing as tools and resources over stdio or Streamable HTTP. Can run as a CLI, a hosted endpoint, or a library inside an existing Node or Next.js site.

Provides AI assistants with direct access to Jamf official documentation, enabling them to answer Jamf-related questions by searching, retrieving articles, and browsing product documentation.

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.

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

Enables access to OpenTelemetry documentation by fetching and converting pages to markdown format and searching content using Google Custom Search. Provides comprehensive documentation lookup and search capabilities for OpenTelemetry concepts, instrumentation, and configuration.

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

Enables coding agents to query a team knowledge base via MCP, performing semantic search and asking questions that return grounded, citation-backed answers from ingested documents.

An MCP server that provides indexed, searchable access to Anthropic Claude and Google Gemini documentation, with full-text search, page fetching, and section listing capabilities.

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 tools to search and retrieve Google Gemini API documentation with full-text search capabilities and automatic documentation updates stored in a local SQLite database.

Enables AI agents to query Linux kernel source code, git history, LKML discussions, Patchwork patches, and documentation with evidence-ranked results, citations, and explicit assumptions or contradictions.

Enables AI assistants to answer Laser SDK and LaserData Cloud questions from current documentation instead of training data, drawing on both the guides website and the public Python API surface. It provides ranked search, full-page retrieval, code example discovery, and related-page navigation across both corpora.

High-performance code understanding toolkit that enables batch reading of multiple files with dependency context, structural outline extraction with Java annotation awareness, and precise location of classes/methods across large codebases.

Enables AI agents to query a device catalog and search SDK method references through read-only MCP tools, allowing natural-language questions about device capabilities and API usage.

Enables users to search, download, and read academic papers from multiple platforms including arXiv, PubMed, bioRxiv, Google Scholar, Semantic Scholar, and CrossRef through a unified interface.

An AI-powered documentation navigator that enables intelligent search, summarization, and exploration of SUSE, Rancher, and related open-source documentation using local or cloud AI models.

Enables MCP-compatible AI clients to query, search, create, and update YApi API definitions and categories using natural language, with write operations excluding deletion for safety.

Enables AI models to search and read technical discussions, customizations, and error resolutions from the Sankhya Community forum. It provides tools to retrieve topic lists and extract clean content from specific posts to help resolve system-related issues.

Enables MCP-compatible clients to search and read local markdown documentation, allowing agents to retrieve relevant doc snippets or full files by path.