Click on "Deploy 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., "@MaxCompute MCP Server list all tables in the MaxCompute project"
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.
A Model Context Protocol (MCP) server for MaxCompute.
Related MCP server: getdot-database-skills
The server offers 4 core tools:
get_latest_partition
Get the latest partition name for a specific table
Input:
table_name (string): Name of the table
Returns: The latest partition name
read_query
Execute a SELECT query on the MaxCompute project, only SELECT query is allowed
Input:
query (string): The SELECT SQL query
Returns: Query results as array of objects
list_tables
List all tables in the MaxCompute project
No input required
Returns: Array of table objects with name and comment
describe_table
Get the schema information for a specific table
Input:
table_name (string): Name of the table
Returns: Raw output of DESC command
Code: GitHub
cd /path/to/maxcompute-mcp-server
uv pip install .
uv build# Add the server to your cline_mcp_settings.json
"mcpServers": {
"maxcompute-mcp-server": {
"command": "uv",
"args": [
"run",
"--with",
"maxcompute-mcp-server",
"maxcompute-mcp-server"
],
"env": {
"ALIBABA_CLOUD_ACCESS_KEY_ID": "",
"ALIBABA_CLOUD_ACCESS_KEY_SECRET": "",
"ALIBABA_CLOUD_MAXCOMPUTE_PROJECT": "",
"ALIBABA_CLOUD_MAXCOMPUTE_ENDPOINT": "https://service.cn-shanghai.maxcompute.aliyun.com/api"
}
}
}Get the schema information for a specific table
| Name | Required | Description | Default |
|---|---|---|---|
| table_name | Yes | Name of the table |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. The description implies a read operation, but does not mention any specific side effects, access requirements, or constraints (e.g., auth needs, rate limits). It is adequate for a simple read but lacks detail.
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 sentence with no unnecessary words. It is front-loaded with the key action and resource.
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?
For a simple read tool with one parameter and no output schema, the description is adequate but minimal. It could mention that it returns column names, types, etc., but the basic purpose is covered.
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?
Schema coverage is 100% (one required parameter 'table_name' with description 'Name of the table'). The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
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?
Description clearly states the tool 'Get the schema information for a specific table', using a specific verb and resource. It distinguishes from sibling tools like list_tables (list all tables) and get_latest_partition (partition info) by focusing on schema details of a single table.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, when not to use, or links to sibling tools like list_tables for overview or read_query for data retrieval.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the latest partition name for a specific table
| Name | Required | Description | Default |
|---|---|---|---|
| table_name | Yes | Name of the table |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose any behavioral traits such as permissions required, handling of tables without partitions, or output format. It only states the basic purpose.
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 sentence and not verbose, but it is too terse, lacking necessary context. It is not optimally useful despite being concise.
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 lack of output schema and annotations, the description is insufficient. It does not explain the return value, edge cases, or any additional context needed for correct usage.
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?
Schema coverage is 100%, providing a baseline of 3. The description adds no additional meaning beyond what the schema already provides for table_name.
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 'Get' and the resource 'latest partition name for a specific table', making the tool's purpose unambiguous. It distinguishes from siblings like describe_table, list_tables, and read_query.
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?
No guidance is provided on when to use this tool versus its siblings. For example, it doesn't mention scenarios like checking the latest partition before querying or alternatives for table metadata.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all tables in the MaxCompute project
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description offers no behavioral details such as permissions, performance impact, or whether it returns metadata. It only states the basic action.
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?
Single sentence, concise and direct. No extraneous information.
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?
For a simple listing tool with no parameters, the description is adequate. It could be improved by hinting at the output (e.g., list of table names).
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?
No parameters, so schema coverage is 100% by default. Description does not need to add parameter details, but it could still mention that no arguments are needed.
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?
Description clearly states the action ('list') and resource ('all tables in the MaxCompute project'). It distinguishes from sibling tools such as describe_table, get_latest_partition, and read_query.
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?
No guidance on when to use this tool versus alternatives. It does not specify prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Execute a SELECT query on the MaxCompute project, only SELECT query is allowed
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The SELECT SQL query |
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 states only that it executes a SELECT query, but omits details such as whether results are returned directly, any limits on query size or execution time, idempotency, or safety. This leaves significant behavioral ambiguity.
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 very concise—one sentence with clear front-loaded verb and object. It contains no fluff, but could include slightly more context without sacrificing conciseness.
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?
Despite the tool's simplicity, the description fails to explain what the output of the query is (e.g., returns result set). Without an output schema, this is a critical gap. It also does not address edge cases or error conditions, leaving the agent underinformed.
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 one parameter 'query' with description 'The SELECT SQL query', providing 100% coverage. The tool description adds 'only SELECT query is allowed', which is redundant with the schema's parameter description. Thus the description adds no new semantic value beyond the schema.
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 'Execute a SELECT query' and the resource 'MaxCompute project'. It also includes the constraint that only SELECT queries are allowed, which clarifies its read-only intent. However, it does not explicitly differentiate from sibling tools like describe_table or list_tables, which also read data but in different ways.
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. It only mentions that SELECT queries are allowed, implying it is not for DDL/DML, but it does not reference sibling tools or describe contexts where each is appropriate.
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.
v0.1.3describe_tableget_latest_partitionlist_tablesread_queryScored across 4 tools
Each tool has a distinct purpose: describing table schema, getting latest partition, listing tables, and executing SELECT queries. No overlap.
All tool names follow a consistent verb_noun pattern with underscores: describe_table, get_latest_partition, list_tables, read_query.
4 tools is reasonable for a focused MaxCompute server covering essential table inspection and querying operations, though some users might expect a few more utility tools.
Covers the main use cases for exploring and querying tables in MaxCompute (list, describe, get latest partition, query). Minor gaps like fetching specific partitions or writing data, but sufficient for typical read-only scenarios.
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