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.
Connects MCP-compatible coding agents to VMware vCenter to query information about virtual machines, hosts, clusters, datastores, datacenters, and networks.
A Model Context Protocol server that allows management of Netlify sites, enabling users to create, list, get information about, and delete Netlify sites directly from an MCP-enabled environment.
MCP server for managing Foreman hosts and infrastructure. Enables listing, searching, and getting detailed information about hosts, organizations, locations, subnets, domains, and more via natural language.
Enables AI assistants to interact with Terraform Cloud workspaces and runs, including checking run status, listing workspaces, and retrieving detailed information about workspaces and runs.
An MCP server for BigQuery that lets Claude answer questions about your search and analytics data, providing real analysis with verdicts and recommendations, not just raw query results.
A local MCP server that lets Claude answer plain-language questions about your Anthropic usage and spend across the developer API platform and Claude Enterprise products.
Mnemosyne is an MCP server that gives AI assistants deep visibility into Kubernetes clusters, enabling natural language queries about cluster state, pods, services, and more.
Enables querying Azure retail pricing information, comparing costs across regions and SKUs, estimating usage-based expenses, and discovering Azure services with savings plan information through the Azure Retail Prices API.
Exposes Moro Hub's services, facilities, and operational data as AI-callable tools, enabling natural language queries about locations, data centre status, support options, and news.
Enables AI-assisted planning inquiries by exposing PP/DS OData APIs as MCP tools for SAP S/4HANA, allowing natural language queries about planned orders, production orders, and work centers.
A Model Context Protocol (MCP) server that interfaces with the Apache YuniKorn Scheduler, allowing AI agents to observe and reason about Kubernetes batch workload resource management, queue hierarchies, and application states.