Emotion Dataset Analysis MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| HF_TOKEN | Yes | Your Hugging Face API token, required to access or download the dataset. |
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_sampleA | Get n random samples from the emotion dataset. Args: n: Number of samples to retrieve (default: 5, max: 20) Returns: JSON string with samples including text and emotion label |
| count_by_emotionA | Count samples for a specific emotion. Args: emotion: One of 'sadness', 'joy', 'love', 'anger', 'fear', 'surprise' Returns: JSON string with count and percentage |
| search_textA | Search for samples containing specific text. Args: query: Text to search for (case-insensitive) limit: Maximum results to return (default: 10) Returns: JSON string with matching samples |
| analyze_emotion_distributionB | Get the distribution of emotions in the dataset. Returns: JSON string with counts and percentages for each emotion |
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 4 tools
The tools have mostly distinct purposes: analyze_emotion_distribution provides overall distribution, count_by_emotion counts specific emotions, get_sample retrieves random samples, and search_text finds text matches. However, analyze_emotion_distribution and count_by_emotion could potentially overlap in functionality since both provide emotion counts, though the former is comprehensive and the latter is specific.
All tool names follow a consistent verb_noun pattern using snake_case: analyze_emotion_distribution, count_by_emotion, get_sample, and search_text. The naming is predictable and readable throughout the set.
With 4 tools, the count is borderline for a dataset analysis server. It covers basic operations but feels thin for comprehensive analysis, lacking tools for filtering, updating, or advanced statistical analysis that might be expected in this domain.
The toolset covers core read operations (distribution analysis, counting, sampling, and searching) but has notable gaps. There are no tools for creating, updating, or deleting dataset entries, and missing advanced features like emotion trend analysis or dataset summarization limit completeness for the stated purpose.