How do I install the ODPS (MaxCompute) Data Query skill?

Run npx skillmds@latest add dvcrn/odps-maxcompute-data-query in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Who published ODPS (MaxCompute) Data Query?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

ODPS (MaxCompute) Data Query by dvcrn

Name: ODPS (MaxCompute) Data Query
Rating: 4.2 (5 reviews)
Author: dvcrn

ODPS (MaxCompute) Data Query

Use this skill when the user wants to query, analyze, or explore data in Alibaba Cloud ODPS (MaxCompute / 阿里云大数据计算服务). This skill executes SQL queries, lists tables, and inspects table schemas by running the odps_helper.py command-line script. Trigger this skill for requests like: querying ODPS data, listing MaxCompute tables, running SQL on ODPS, checking table structure, analyzing business data stored in ODPS, or any data exploration tasks involving Alibaba Cloud MaxCompute / ODPS.

dvcrn Updated Sep 8, 2026 32 repo stars

File contents

Setup (First-time only)

Copy the credential template and fill in your values:

cd mcp-odps/
cp config.example.env .env
# Edit .env with your Alibaba Cloud credentials

Activate your Python environment and install dependency:

# conda users:
conda activate <your-env>
# venv users:
source .venv/bin/activate

pip install pyodps

Executing Commands

Activate your Python environment first, then run all commands from the project root with:

SCRIPT=mcp-odps/scripts/odps_helper.py

List tables

python $SCRIPT --list-tables

Filter by name:

python $SCRIPT --list-tables --pattern <keyword>

Get table schema

python $SCRIPT --describe <table_name>

Execute SQL query

python $SCRIPT --query "<SQL statement>" [--limit <n>]

Default limit is 100 rows.

Workflow for Data Tasks

Follow this pattern when the user asks about ODPS data:

Discover — If the table name is unknown, run --list-tables --pattern <keyword> to find it.
Inspect — Run --describe <table> to understand columns, types, and partition structure.
Query — Construct the SQL and run --query. Always add a partition filter (WHERE dt = '...') for partitioned tables to avoid full scans.
Present — Summarize the results clearly for the user.

ODPS SQL Key Differences from Standard SQL

Feature	Standard SQL	ODPS SQL
String concat	`a \|\| b`	`CONCAT(a, b)`
Current time	`NOW()`	`GETDATE()`
Null coalesce	`IFNULL(x,y)`	`NVL(x, y)`
Regex match	`REGEXP`	`RLIKE`
Date literal	`'2024-01-01'`	`TO_DATE('2024-01-01','yyyy-mm-dd')`

Partition filter is required for partitioned tables (partition column is usually dt):

SELECT * FROM table_name WHERE dt = '2024-01-01' LIMIT 100

See mcp-odps/references/odps_sql_guide.md for a full SQL reference.

Error Handling

pyodps not found → Run install command in Setup step above
Missing credentials → Check that mcp-odps/.env exists and all four fields are filled in
Table not found → Use --list-tables --pattern to find the correct name
SQL syntax error → Check the ODPS SQL differences table above; avoid MySQL/PostgreSQL-specific syntax

---name: odps-maxcompute-data-querydescription: Use this skill when the user wants to query, analyze, or explore data in Alibaba Cloud ODPS (MaxCompute / 阿里云大数据计算服务). This skill executes SQL queries, lists tables, and inspects table schemas by running the odps_helper.py command-line script. Trigger this skill for requests like: querying ODPS data, listing MaxCompute tables, running SQL on ODPS, checking table structure, analyzing business data stored in ODPS, or any data exploration tasks involving Alibaba Cloud MaxCompute / ODPS.---## Setup (First-time only)1. Copy the credential template and fill in your values: ```bash cd mcp-odps/ cp config.example.env .env # Edit .env with your Alibaba Cloud credentials ```2. Activate your Python environment and install dependency: ```bash # conda users: conda activate <your-env> # venv users: source .venv/bin/activate pip install pyodps ```## Executing CommandsActivate your Python environment first, then run all commands from the project root with:```bashSCRIPT=mcp-odps/scripts/odps_helper.py```### List tables```bashpython $SCRIPT --list-tables```Filter by name:```bashpython $SCRIPT --list-tables --pattern <keyword>```### Get table schema```bashpython $SCRIPT --describe <table_name>```### Execute SQL query```bashpython $SCRIPT --query "<SQL statement>" [--limit <n>]```Default limit is 100 rows.## Workflow for Data TasksFollow this pattern when the user asks about ODPS data:1. **Discover** — If the table name is unknown, run `--list-tables --pattern <keyword>` to find it.2. **Inspect** — Run `--describe <table>` to understand columns, types, and partition structure.3. **Query** — Construct the SQL and run `--query`. Always add a partition filter (`WHERE dt = '...'`) for partitioned tables to avoid full scans.4. **Present** — Summarize the results clearly for the user.## ODPS SQL Key Differences from Standard SQL| Feature | Standard SQL | ODPS SQL ||---------|-------------|----------|| String concat | `a \|\| b` | `CONCAT(a, b)` || Current time | `NOW()` | `GETDATE()` || Null coalesce | `IFNULL(x,y)` | `NVL(x, y)` || Regex match | `REGEXP` | `RLIKE` || Date literal | `'2024-01-01'` | `TO_DATE('2024-01-01','yyyy-mm-dd')` |Partition filter is **required** for partitioned tables (partition column is usually `dt`):```sqlSELECT * FROM table_name WHERE dt = '2024-01-01' LIMIT 100```See `mcp-odps/references/odps_sql_guide.md` for a full SQL reference.## Error Handling- **`pyodps` not found** → Run install command in Setup step above- **Missing credentials** → Check that `mcp-odps/.env` exists and all four fields are filled in- **Table not found** → Use `--list-tables --pattern` to find the correct name- **SQL syntax error** → Check the ODPS SQL differences table above; avoid MySQL/PostgreSQL-specific syntax

Frequently asked questions