"General information about clusters" matching MCP servers:

he industry standard reference for safe, observable, and steerable AI agent UX. Browse and search 10 Blueprint principles, clusters, curated implementation examples, and application guides. 13 public tools require no credentials.

Enables AI agents to interact with Kubernetes clusters through progressive disclosure, where agents discover TypeScript modules via filesystem, write and execute code, and receive summarized console output for cluster management tasks.

Search and discover AI agents, skills, prompts, bundles and MCP connectors from a curated catalog of 4500+ assets. Provides tools for searching, browsing categories, and accessing detailed information about each asset.

MCP server that lets Claude Code delegate heavy tasks (file analysis, deep search, web lookups, adversarial review, and general delegation) to the Antigravity CLI (agy), with model routing, session continuity, timeout controls, and quota-aware failover.

mcp-server-couchbase

Provides AI assistants with real-time access to the AGNO framework documentation by enabling them to browse, search, and fetch documentation pages. This server allows users to query information about AGNO's Agents, Teams, and Workflows directly through MCP-compatible clients.

Enables AI agents to consult with multiple AI models (GPT, Gemini, Grok, etc.) through OpenRouter with intelligent auto-selection, conversation history, and caching. Allows your AI assistant to seek expert opinions from specialized models for different tasks like coding, analysis, or general questions.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

MCP server for SkyPilot that lets LLMs manage cloud clusters, jobs, and storage through the Model Context Protocol.

A gateway for Generative AI systems to interact with multiple Kubernetes clusters through Model Context Protocol, enabling comprehensive Kubernetes resource operations and multi-cluster management.

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

A server that implements the Model Completion Protocol (MCP) to allow LLMs to interact with Databricks resources including clusters, jobs, notebooks, and SQL execution through natural language.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

A lightweight topological arbitration MCP server for multi-agent clusters, using Topological Data Analysis to resolve decision conflicts and enable consensus among agents.

A server that enables AI models to access user geolocation information via EdgeOne Pages Functions through the Model Context Protocol.

An MCP server that enables interaction with Kubernetes/Minikube clusters through natural language, allowing AI agents like Codename Goose to manage Kubernetes resources via the Model Context Protocol.

Enables Cursor agents to communicate via a shared chat room, allowing them to ask questions, share status, and warn about conflicts while collaborating on the same repo.

A general-purpose MCP connectivity layer that bridges MCP clients to authenticated remote MCP servers, managing authentication, credentials, routing, and connection lifecycle. It enables clients like OpenHands Cloud to securely connect to remote MCP servers such as Notion.

Enables read-only access to Pocket Agent's product information, public persona templates, and app catalog. No authentication required.

Enables AI models to access user geolocation information through EdgeOne Pages Functions, allowing location-aware AI interactions.