"Understanding Gaode Map MCP" matching MCP servers:

An MCP server that enables any AI agent to call Claude using your existing Max/Pro subscription via OAuth, avoiding additional API billing.

A lightweight, zero-dependency Python MCP server that exposes a single do_everything tool. Any AI agent that supports MCP can use it to offload all language-model work to a local OpenAI-compatible endpoint, reducing cost on the agent's primary LLM.

An MCP server that enables AI agents to safely operate multi-cluster Kubernetes fleets through an Open Cluster Management hub, with policy enforcement, human approval, and audit tracing.

Orchestrate parallel Claude agent workloads via Docker containers with combinators for parallel execution, map-reduce, and pipeline workflows.

An MCP server for task orchestration.

Allows AI to interact with Autodesk Revit via the MCP protocol, enabling retrieval of project data and automation of tasks like creating, modifying, and deleting elements.

An MCP server that transforms AI assistants into personal chefs by providing recipe recommendations and meal planning features based on the HowToCook repository.

MCP Compass is a discovery and recommendation service that assists AI assistants in finding and understanding Model Context Protocol servers through natural language queries.

A bridge server that connects Agent Communication Protocol (ACP) agents with Model Context Protocol (MCP) clients, enabling seamless integration between ACP-based AI agents and MCP-compatible tools like Claude Desktop.

Non-official Model Context Protocol server that enables interaction with AMap's location services through clients like Cursor, Claude Desktop, Cline, and Windsurf.

A dynamic service that creates and manages Model Context Protocol (MCP) servers, allowing users to spawn, customize, and control multiple MCP servers as child processes.

Enables Google Antigravity CLI to offload token-heavy workloads to local Ollama models through MCP tools for code drafting, summarization, chunked map-reduce, and JSON extraction, reducing cloud token usage.

A Model Context Protocol (MCP) server that demonstrates how to build and implement custom tools for Claude using the mcp-framework.

Enables AI assistants to interact with Google Cloud Platform resources through natural language queries. Supports querying and managing GCP services like Compute Engine, Cloud Storage, BigQuery, and more across multiple projects and regions.

Monitors and analyzes interactions between MCP servers to detect emergent patterns, visualize coupling relationships, and suggest optimal next actions based on system coherence and resonance state.

An MCP gateway that automatically turns Django REST Framework ViewSets into callable MCP tools with zero boilerplate, featuring a token-efficient dispatcher pattern to minimize context usage.

🚀 Tigris MCP Server implements the MCP specification to create a seamless connection between AI agents and Tigris key features like bucket and object management.

A proxy MCP server that aggregates tools from multiple MCP servers and forwards calls to the appropriate server, used with the Metatool App for GUI tool management.

Governs AI agent tool calls by checking them against Agentic Control Plane policies, returning allow/deny/ask decisions with audit logging and identity attribution for MCP clients like Claude and ChatGPT. Exposes acp_check and acp_status tools for policy enforcement and connection verification.

A central hub that aggregates multiple MCP resource servers into a single unified interface, enabling users to access tools and capabilities from multiple backend servers through one connection point.