A Model Context Protocol (MCP) server implementation that enables comprehensive configuration and management of Higress. This repository also provides an MCP client built on top of LangGraph and LangChain MCP Adapters, facilitating interaction with the Higress MCP Server through a well-designed agent flow architecture. Copy the .env.example file to .env and fill in the corresponding values. In std
Add this skill
npx mdskills install higress-group/higress-ops-mcp-serverWell-structured MCP server for Higress management with extensible architecture and clear tool guidelines
A Model Context Protocol (MCP) server implementation that enables comprehensive configuration and management of Higress. This repository also provides an MCP client built on top of LangGraph and LangChain MCP Adapters, facilitating interaction with the Higress MCP Server through a well-designed agent flow architecture.
https://github.com/user-attachments/assets/bae66b77-a158-452e-9196-98060bac0df7
Copy the .env.example file to .env and fill in the corresponding values.
In stdio mode, the MCP server process is started by the MCP client program. Run the following command to start the MCP client and MCP server:
uv run client.py
Step 1: Create a new tool class or extend an existing one
from typing import Dict, List, Any
from fastmcp import FastMCP
class YourTools:
def register_tools(self, mcp: FastMCP):
@mcp.tool()
async def your_tool_function(arg1: str, arg2: int) -> List[Dict]:
"""
Your tool description.
Args:
arg1: Description of arg1
arg2: Description of arg2
Returns:
Description of the return value
Raises:
ValueError: If the request fails
"""
# Implementation using self.higress_client to make API calls
return self.higress_client.your_api_method(arg1, arg2)
Step 2: Add a new method to HigressClient if your tool needs to interact with the Higress Console API
def your_api_method(self, arg1: str, arg2: int) -> List[Dict]:
"""
Description of what this API method does.
Args:
arg1: Description of arg1
arg2: Description of arg2
Returns:
Response data
Raises:
ValueError: If the request fails
"""
path = "/v1/your/api/endpoint"
data = {"arg1": arg1, "arg2": arg2}
return self.put(path, data) # or self.get(path) or self.post(path, data)
Step 3: Register your tool class in the server
tool_classes = [
CommonTools,
RequestBlockTools,
RouteTools,
ServiceSourceTools,
YourTools # Add your tool class here
]
Step 4: Add your tool to SENSITIVE_TOOLS if it requires human confirmation
# Define write operations that require human confirmation
SENSITIVE_TOOLS = [
"add_route",
"add_service_source",
"update_route",
"update_request_block_plugin",
"update_service_source",
"your_tool_function" # Add your tool name here if it requires confirmation
]
Install via CLI
npx mdskills install higress-group/higress-ops-mcp-serverHigress OPS MCP Server is a free, open-source AI agent skill. A Model Context Protocol (MCP) server implementation that enables comprehensive configuration and management of Higress. This repository also provides an MCP client built on top of LangGraph and LangChain MCP Adapters, facilitating interaction with the Higress MCP Server through a well-designed agent flow architecture. Copy the .env.example file to .env and fill in the corresponding values. In std
Install Higress OPS MCP Server with a single command:
npx mdskills install higress-group/higress-ops-mcp-serverThis downloads the skill files into your project and your AI agent picks them up automatically.
Higress OPS MCP Server works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Gemini Cli, Amp, Roo Code, Goose. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.