Sanshu is an open-source binary MCP that automates operations tasks. It connects to Claude agents to streamline workflows, reducing manual effort and improving efficiency for operations teams.
git clone https://github.com/yuaotian/sanshu.gitSanshu is an open-source binary MCP that automates operations tasks. It connects to Claude agents to streamline workflows, reducing manual effort and improving efficiency for operations teams.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/yuaotian/sanshuCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Help me automate a workflow using sanshu. I need to [TASK] for my [COMPANY] in the [INDUSTRY] sector. Provide a step-by-step guide with code snippets where necessary.
## Automating Data Processing with sanshu
### Step 1: Installation
To get started, you'll need to install sanshu. Open your terminal and run the following command:
```bash
pip install sanshu
```
### Step 2: Setting Up Your Workflow
Next, create a new Python script and import the sanshu library:
```python
import sanshu
```
### Step 3: Defining Your Task
Let's say you want to automate data cleaning for your company's sales data. You can define your task as follows:
```python
def clean_sales_data(data):
# Your data cleaning logic here
return cleaned_data
```
### Step 4: Running Your Workflow
Finally, run your workflow by calling the `clean_sales_data` function with your data:
```python
sales_data = ["data1", "data2", "data3"]
cleaned_data = clean_sales_data(sales_data)
```
By following these steps, you can automate your data cleaning process using sanshu.Simple data integration for modern teams
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