"A server for finding information about Google Ads" matching MCP servers:

Enables extracting explicitly stated contract metadata, clauses, and obligations from user-supplied contract text without storing or modifying the data.

Provides seamless access to the NASA Astrophysics Data System (ADS) for searching astronomical papers, tracking citations and metrics, managing paper libraries, and exporting BibTeX references through natural language conversation.

Local multi-version RAG MCP server for Keysight ADS help documentation, enabling search, AEL function lookup, and version comparison via natural language.

Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.

Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.

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

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

Enables querying documents through a Langflow backend using natural language questions, providing an interface to interact with Langflow document Q\&A flows.

A tool that helps users conduct comprehensive research on complex topics by exploring questions in depth, finding relevant sources, and generating structured, well-cited research reports.

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.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

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.

An MCP server that retrieves and cleans official documentation for popular AI/Python libraries via web search and LLM processing, exposing a get_docs tool.

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.

Provides Large Language Models with real-time access to the latest documentation for Python libraries like Langchain, LlamaIndex, and OpenAI, enabling accurate and up-to-date code suggestions.

Provides access to developer roadmap content from roadmap.sh, allowing users to list available roadmaps and fetch detailed Markdown content for specific career paths.

Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

A read-only MCP server providing curated Qdrant documentation for LLMs, enabling retrieval of the latest and most accurate documentation.

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.