"Information and Resources for Terraform AWS Integration" matching MCP servers:

Provides hybrid (BM25 + vector) search over Terraform AWS and Google provider documentation, with tools for ranked search and full document retrieval.

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

Enables AI assistants to search and retrieve information about Terraform providers and modules from the public Terraform registry, including detailed documentation, version information, and resource specifications.

Enables searching and reading AWS knowledge from sources the official AWS Knowledge MCP Server does not index, including re:Post community Q&A, kiro.dev documentation, and AWS Builder Center posts.

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.

Enables access to AWS documentation through natural language by fetching and converting documentation pages to markdown, searching AWS docs, and getting content recommendations for AWS service documentation.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

A Model Context Protocol (MCP) server that enables searching AWS Black Belt Online Seminars and retrieving their transcripts.

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.

Provides real-time access to AWS security best practices, incident response playbooks, and preventive security measures from the official AWS Customer Playbook Framework repository. Enables users to query AWS security guidance for services like S3, IAM, EC2, and RDS through 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.

Provides comprehensive documentation about AWS AgentCore framework to GenAI tools, enabling users to build production-ready AI agents with enterprise-grade security, observability, and scalability. Offers guidance on identity management, API integration, monitoring, code execution, memory storage, and tool integration for AI agents.

A collection of MCP servers for Slack, Jira, Confluence, and release coordination to automate QA workflows and daily release status reporting.

Medicare claim documentation lookup for CPT codes against live CMS sources, returning structured requirements and document URIs with optional enrichment via RCI APIs.

Integrates PTC Windchill and Creo Parametric with LLM-based clients via the Model Context Protocol, enabling natural language interaction with PLM and CAD systems for tasks like part search, BOM retrieval, model operations, and exports.

Enables searching AWS Amplify documentation using natural language queries with advanced search syntax, smart ranking, and generation selection.

An MCP server that provides comprehensive access to AWS Amplify Gen 2 Next.js documentation, enabling AI assistants to provide accurate, up-to-date guidance on building applications with Amplify.

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.

Enables AI assistants to search and retrieve documentation, component specs, theme guides, and CLI commands for the Meta Astryx Design System, providing structured tools and guidelines for coding agents.

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.