MCP Mix Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ANTHROPIC_API_KEY | Yes | Your Anthropic API access key |
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 |
|---|---|
| summarize_csv_fileA | Summarise a CVS file by reporting its number of rows and columns. Args: filename (str): Name of the CSV file in the /data directory. Returns: str: A string describing the file's dimensions. |
| summarize_parquet_fileA | Summarise a Parquet file by reporting its number of rows and columns. Args: filename (str): Name of the Parquet file in the /data directory. Returns: str: A string describing the file's dimensions. |
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 2 tools
The two tools have clearly distinct purposes: one handles CSV files and the other handles Parquet files. There is no overlap or ambiguity in their functionality, as each is specialized for a different file format.
Both tools follow a consistent verb_noun pattern with 'summarize' as the verb and the file type as the noun (csv_file, parquet_file). The naming is perfectly uniform and predictable across the set.
With only 2 tools, the server feels thin for a 'Mix Server' that implies broader data processing capabilities. The scope is limited to summarizing two specific file formats, which may not justify the server's name or provide comprehensive coverage for data analysis tasks.
The tool surface is severely incomplete for data processing. It only offers summarization for CSV and Parquet files, lacking essential operations like reading, writing, filtering, transforming, or handling other common formats (e.g., JSON, Excel). This will likely cause agent failures in broader workflows.