Higress OPS MCP Server
Model Context Protocol server and client for fully managed Higress configuration.
Key Features
Use Cases
README
Higress OPS MCP Server
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.
Demo
https://github.com/user-attachments/assets/bae66b77-a158-452e-9196-98060bac0df7
Config Environment Variables
Copy the .env.example file to .env and fill in the corresponding values.
Start MCP Client and MCP Server
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
Add a new tool
Step 1: Create a new tool class or extend an existing one
- Create a new file in the tools directory if adding a completely new tool category
- Or add your tool to an existing class if it fits an existing category
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
- Add methods to utils/higress_client.py that encapsulate API calls
- Use the existing HTTP methods (get, put, post) for actual API communication
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
- Add your tool class to the tool_classes list in server.py
- This list is used by ToolsRegister to instantiate and register all tools
- The ToolsRegister will automatically set logger and higress_client attributes
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
- Tools in this list will require human confirmation before execution
# 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
]
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