Provides tools for querying SLS (Simple Log Service) logs, with planned future support for managing ECS instances and deploying serverless functions on Alibaba Cloud.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Aliyun MCP Server show me error logs from my-project/my-logstore for the last 30 minutes"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
This MCP server provides tools for interacting with Aliyun (Alibaba Cloud) services through Claude.
Query SLS (Simple Log Service) logs
(Future) Manage ECS instances
(Future) Deploy serverless functions
Related MCP server: CLS MCP Server
Build the server:
npm install
npm run buildAdd the server to your claude_desktop_config.json:
{
"mcpServers": {
"aliyun": {
"command": "node",
"args": ["/path/to/aliyun-mcp-server/build/index.js"],
"env": {
"ALIYUN_ACCESS_KEY_ID": "your-access-key-id",
"ALIYUN_ACCESS_KEY_SECRET": "your-access-key-secret",
"SLS_ENDPOINT": "cn-hangzhou.log.aliyuncs.com"
},
"disabled": false,
"autoApprove": []
}
}
}Add the server to your Cline MCP settings file inside VSCode's settings cline_mcp_settings.json
{
"mcpServers": {
"aliyun": {
"command": "node",
"args": ["/path/to/aliyun-mcp-server/build/index.js"],
"env": {
"ALIYUN_ACCESS_KEY_ID": "your-access-key-id",
"ALIYUN_ACCESS_KEY_SECRET": "your-access-key-secret",
"SLS_ENDPOINT": "cn-hangzhou.log.aliyuncs.com"
},
"disabled": false,
"autoApprove": []
}
}
}Replace /path/to/aliyun-mcp-server with the actual path to this repository, and provide your Aliyun credentials.
Once configured, you can ask Claude to query SLS logs:
Query SLS logs from project "my-project" and logstore "my-logstore" with the query "error" for the last hour.Claude will use the MCP server to execute the query and return the results.
Query Aliyun SLS (Simple Log Service) logs.
Parameters:
project (required): SLS project name
logstore (required): SLS logstore name
query (required): SLS query statement
from (optional): Start time in milliseconds (defaults to 1 hour ago)
to (optional): End time in milliseconds (defaults to now)
limit (optional): Maximum number of logs to return (default: 100, max: 1000)
offset (optional): Offset for pagination (default: 0)
reverse (optional): Whether to return results in reverse order (default: false)
Example:
{
"project": "my-project",
"logstore": "my-logstore",
"query": "error",
"limit": 10
}Query Aliyun SLS (Simple Log Service) logs
| Name | Required | Description | Default |
|---|---|---|---|
| from | No | Start time in milliseconds (defaults to 1 hour ago) | |
| limit | No | Maximum number of logs to return (default: 100, max: 1000) | |
| logstore | Yes | SLS logstore name | |
| offset | No | Offset for pagination (default: 0) | |
| project | Yes | SLS project name | |
| query | Yes | SLS query statement | |
| reverse | No | Whether to return results in reverse order (default: false) | |
| to | No | End time in milliseconds (defaults to now) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions querying logs but fails to describe key behaviors such as authentication requirements, rate limits, error handling, or the format of returned results, leaving significant gaps for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core function without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of an 8-parameter log querying tool with no annotations and no output schema, the description is insufficient. It lacks details on behavior, results format, and usage context, making it incomplete for effective agent operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting all 8 parameters with defaults and constraints. The description adds no additional parameter semantics beyond the schema, so it meets the baseline for adequate but not enhanced coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'query' and the resource 'Aliyun SLS (Simple Log Service) logs', making the purpose specific and understandable. However, with no sibling tools mentioned, it lacks explicit differentiation from potential alternatives, though this is not a fault given the context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or context for its application. It merely states what it does without indicating scenarios or constraints for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0querySLSLogsWith only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as querying Aliyun SLS logs, making it distinct by default.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'querySLSLogs' follows a clear verb_noun pattern, and there are no other tools to compare it against for inconsistency.
A single tool is too few for a server named 'Aliyun MCP Server', which implies broader cloud service functionality. This minimal toolset severely limits the server's scope and utility, making it feel incomplete and underpowered for its apparent purpose.
The server appears to target Aliyun cloud services, but with only a log querying tool, there are significant gaps in coverage. Missing are core operations like managing resources (e.g., creating/deleting instances), monitoring, or other SLS functions beyond querying, making the surface severely incomplete.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Connects AI assistants to CloudQuell multi-cloud and AI cost, savings, anomaly, and budget data.
Deploy, monitor, and manage your OpenClaw AI assistants via natural language.
Connect Claude to your Platform7n workspaces — chat, links, and tasks. One-click OAuth.
AI Visibility and Content Intelligence tools for Claude and MCP-compatible agents.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/nailuoGG/aliyun-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server
