Retrieve actions for a resource managed by an application in ArgoCD. Specifies the application name, namespace, and resource details to list applicable actions.
Retrieve available facets for filtering cloud resources by provider, enabling efficient resource management and security insights in Kubernetes and cloud environments.
Generate a workspace by specifying an instance type and cloud provider, enabling efficient deployment and management of ML models on Brev's MCP server.
Retrieve managed resources for a specific ArgoCD application by name, with optional filters to narrow results by kind, namespace, name, API version, group, application namespace, or project. This helps handle large applications efficiently while avoiding token limits.
A static MCP server that helps AI models maintain tool context across chat sessions, preventing loss of important information and keeping conversations smooth and uninterrupted.
Provides persistent tool context that survives across Claude Desktop chat sessions, automatically injecting tool-specific rules, syntax preferences, and best practices. Eliminates the need to re-establish context in each new conversation.
Enables AI models to seamlessly access and query local markdown technical documentation files, providing automatic documentation context without explicit prompting.