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Text Count Mcp Server
What is Text Count Mcp Server
text-count-mcp-server is a Model Context Protocol server designed to provide text counting tools for AI models, enabling accurate counting of characters and words in text without relying on the models’ own counting abilities.
Use cases
Use cases include integrating with AI models for text analysis, developing applications that require character and word counting, and enhancing text processing capabilities in software solutions.
How to use
To use text-count-mcp-server, you can run it as a standalone server using the command ‘node build/index.js’ after installation with ‘npm install’. It can also be used with any MCP-compatible client.
Key features
Key features include ‘count_characters’ for counting the number of characters in a text string and ‘count_words’ for counting the number of words in a text string, currently supporting English and other space-delimited languages.
Where to use
text-count-mcp-server can be used in various fields such as natural language processing, AI development, and any application requiring precise text analysis.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Text Count Mcp Server
text-count-mcp-server is a Model Context Protocol server designed to provide text counting tools for AI models, enabling accurate counting of characters and words in text without relying on the models’ own counting abilities.
Use cases
Use cases include integrating with AI models for text analysis, developing applications that require character and word counting, and enhancing text processing capabilities in software solutions.
How to use
To use text-count-mcp-server, you can run it as a standalone server using the command ‘node build/index.js’ after installation with ‘npm install’. It can also be used with any MCP-compatible client.
Key features
Key features include ‘count_characters’ for counting the number of characters in a text string and ‘count_words’ for counting the number of words in a text string, currently supporting English and other space-delimited languages.
Where to use
text-count-mcp-server can be used in various fields such as natural language processing, AI development, and any application requiring precise text analysis.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
text-count-mcp-server
A Model Context Protocol (MCP) server that provides text counting tools for AI models.
Overview
This server implements the Model Context Protocol to provide tools for counting characters and words in text. These tools help AI models to accurately count text elements without relying on their own counting abilities.
Features
- count_characters: Count the number of characters in a text string
- count_words: Count the number of words in a text string (currently supports English and other space-delimited languages)
Installation
npm install
Usage
As a standalone server
node build/index.js
With an MCP-compatible client
This server can be used with any client that supports the Model Context Protocol.
API
count_characters
Counts the number of characters in the provided text.
Input:
{
"text": "The text to count characters in."
}
Output:
{
"content": [
{
"type": "text",
"text": "The text contains 30 characters."
}
]
}
count_words
Counts the number of words in the provided text.
Input:
{
"text": "The text to count words in."
}
Output:
{
"content": [
{
"type": "text",
"text": "The text contains 6 words."
}
]
}
Limitations
- Japanese language word counting is not yet supported.
- Other languages use space-based word splitting, which may not be accurate for all languages.
License
See the LICENSE file for license rights and limitations.
DevTools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.