MCP Word Counter
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 |
|---|---|
| analyze_textC | Count words and characters in a text document |
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 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'analyze_text' has a single, clearly defined purpose of counting words and characters, so an agent cannot misselect between non-existent alternatives.
A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'analyze_text' follows a clear verb_noun pattern, which would be consistent if more tools were added.
The server 'MCP Word Counter' has only one tool, which feels thin for its apparent scope of text analysis. While word and character counting is a specific task, a typical text analysis server might include additional tools (e.g., for sentiment, readability, or language detection) to provide more comprehensive functionality.
The tool set is severely incomplete for a text analysis domain. It only covers basic word and character counting, with obvious gaps such as sentence counting, paragraph analysis, frequency analysis, or other common text metrics. This limited surface will likely cause agent failures when more advanced text processing is needed.