MCP Data Wrangler
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| data_shapeD | Data shape of the input data |
| data_schemaD | Data schema of the input data |
| describe_dataC | Summary statistics of the input data |
| data_estimated_sizeC | Estimated size of the input data |
| data_countC | Number of non-null elements for each column |
| data_maxC | Maximum values for each column |
| data_max_horizontalC | Maximum values across columns for each row |
| data_minC | Minimum values for each column |
| data_min_horizontalC | Minimum values across columns for each row |
| data_meanC | Mean values for each column |
| data_mean_horizontalC | Mean values across columns for each row |
| data_medianC | Median values for each column |
| data_productC | Product values for each column |
| data_quantileC | Quantile values for each column |
| data_stdC | Standard deviation values for each column |
| data_varC | Variance values for each column |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 16 tools
Every tool has a clearly distinct purpose focused on specific statistical calculations or data structure analysis. The tools are well-differentiated by their mathematical functions (mean, median, std, var, etc.) and orientation (column vs. horizontal), with no ambiguity about which tool to use for each operation.
All tools follow a consistent 'data_' prefix with descriptive suffixes that clearly indicate their function. The naming pattern is uniform throughout (snake_case, descriptive terms), making it easy to understand what each tool does from its name alone.
Sixteen tools is slightly high but reasonable for a comprehensive data analysis toolkit. The server covers extensive statistical operations, which justifies the count, though some tools like data_product might be less commonly used compared to core statistics.
The toolset provides complete coverage for data wrangling and statistical analysis, including descriptive statistics (mean, median, std, var), data structure inspection (schema, shape), and specialized calculations (quantiles, horizontal operations). There are no obvious gaps for this domain.