A

Alibaba Cloud Observability

The Alibaba Cloud Observable MCP Service provides a series of tools to access products such as Alibaba Cloud Log Service SLS and Application Real - time Monitoring Service ARMS. It supports functions such as natural language to query conversion, log analysis, and performance monitoring.
2.5 points
23

What is the Alibaba Cloud Observable MCP Service?

This is a bridge service that connects intelligent assistants with Alibaba Cloud observability products. It provides tools such as log query, application monitoring, and performance analysis, allowing you to obtain the running status of cloud systems through natural language.

How to use this service?

Simply install the Python package and configure your Alibaba Cloud access keys, and you can connect to various AI assistant tools via SSE or the command line.

Applicable scenarios

Suitable for scenarios where cloud resources need to be monitored, such as operations personnel quickly troubleshooting problems, developers analyzing application performance, and business personnel viewing operational indicators.

Main features

Log analysis toolsetSupports full - link log analysis functions such as log project/repository retrieval, SQL query generation, and query diagnosis.
Application performance monitoringProvides APM capabilities such as application discovery, call chain query, and flame graph analysis, and supports applications such as Java/Go.
Natural language to query conversionAutomatically converts daily language into professional SLS SQL or PromQL query statements.

Advantages and limitations

Advantages
No need to learn professional query syntax. You can obtain monitoring data through natural language.
Integrates multiple Alibaba Cloud observability products in one - stop.
Supports seamless integration with mainstream AI tools such as Cursor/ChatWise.
Limitations
Currently, it only fully supports Log Service (SLS), and the functions of other products are being gradually integrated.
Complex queries may require manual optimization of the generated SQL statements.

How to use

Obtain Alibaba Cloud access keys
Log in to the Alibaba Cloud console and create an AccessKey with appropriate permissions on the RAM access control page.
Install the service package
Install the latest version of the MCP service package via pip.
Start the service
Choose SSE (Server - Sent Events) or STDIO (Standard Input/Output) to run the service.

Usage examples

Troubleshoot application errorsWhen an application has an exception, describe the error phenomenon in natural language to automatically query relevant logs and call chains.
Performance optimization analysisCompare the CPU usage before and after the release of a new version to locate performance bottlenecks.

Frequently Asked Questions

How to control the amount of data returned by a query?
Why can't some log fields be queried?
Which languages are supported for flame graph analysis?

Related resources

Alibaba Cloud Log Service Documentation
Official SLS product documentation and API reference
GitHub Source Code Repository
Open - source project code and update logs
Permission Configuration Guide
Suggestions for minimizing RAM permissions
Installation
Copy the following command to your Client for configuration
{
  "mcpServers": {
    "alibaba_cloud_observability": {
      "url": "http://localhost:7897/sse"
        }
  }
}

{
  "mcpServers": {
    "alibaba_cloud_observability": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/your/alibabacloud-observability-mcp-server",
        "run",
        "mcp-server-aliyun-observability"
      ],
      "env": {
        "ALIBABA_CLOUD_ACCESS_KEY_ID": "<your_access_key_id>",
        "ALIBABA_CLOUD_ACCESS_KEY_SECRET": "<your_access_key_secret>"
      }
    }
  }
}

{
  "mcpServers": {
    "alibaba_cloud_observability": {
      "command": "uv",
      "args": [
        "run",
        "mcp-server-aliyun-observability"
      ],
      "env": {
        "ALIBABA_CLOUD_ACCESS_KEY_ID": "<your_access_key_id>",
        "ALIBABA_CLOUD_ACCESS_KEY_SECRET": "<your_access_key_secret>"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.
K
Kubernetes
An MCP server based on Kubernetes for managing and operating Kubernetes clusters
TypeScript
553
5 points
E
Edgeone Pages MCP Server
EdgeOne Pages MCP is a service that quickly deploys HTML content to EdgeOne Pages via the MCP protocol and obtains a public URL
TypeScript
260
4.8 points
A
Awslabs Cost Analysis MCP Server
The AWS MCP Servers are a set of dedicated servers based on the Model Context Protocol, offering various AWS-related functions, including document retrieval, knowledge base query, CDK best practices, cost analysis, image generation, etc., aiming to enhance the integration of AI applications with AWS services through a standardized protocol.
Python
2.6K
5 points
2
2344
Opik is an open-source LLM evaluation framework that supports tracking, evaluating, and monitoring LLM applications, helping developers build more efficient and cost-effective LLM systems.
TypeScript
7.1K
5 points
M
MCP K8s Go
An MCP server based on Golang for connecting to Kubernetes clusters, providing resource query and operation functions.
Go
318
4 points
S
Solon
Solon is an efficient, open, and eco - friendly Java enterprise application development framework that supports all - scenario development. It features high performance, low memory consumption, fast startup, and small - volume packaging. It is compatible with Java 8 to Java 24 and the GraalVM native runtime.
Java
2.5K
5 points
K
Kubectl MCP Server
The Kubectl MCP Tool is a Kubernetes interaction tool based on the Model Context Protocol (MCP), allowing AI assistants to interact with Kubernetes clusters using natural language.
Python
423
4.5 points
K
Kubernetes Manager
A Kubernetes cluster management server based on the MCP protocol, supporting interaction with the Kubernetes cluster through the command line or chat interface, providing functions such as resource management and Helm chart operations.
TypeScript
568
5 points
Featured MCP Services
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
1.7K
5 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
97
4.3 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
150
4.5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
838
4.3 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
6.7K
4.5 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
573
5 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
5.2K
4.7 points
G
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
289
4.5 points
AIbase
Zhiqi Future, Your AI Solution Think Tank
© 2025AIbase