MCP Character Tools
M

MCP Character Tools

MCP Character Tools is a server that provides character - level text analysis capabilities for large language models, solving the problem that LLMs have difficulty handling individual characters due to word segmentation, and offering more than 14 tools for character counting, spelling analysis, and text comparison.
2.5 points
8.5K

What is MCP Character Tools?

MCP Character Tools is a tool server specifically designed for large language models, which provides more than 14 types of character and text analysis functions. Since AI models usually break text into sub - words (e.g.,'strawberry' may be split into'straw' and 'berry'), they have difficulty directly handling individual characters. This toolset enables AI to'see' content at the character level and accurately perform tasks such as counting the number of letters and analyzing text structure.

How to use MCP Character Tools?

You can use these tools through AI applications that support the MCP protocol, such as Claude Desktop. After installation, the AI assistant will automatically gain character analysis capabilities. You can directly ask questions such as 'How many r's are there in 'garlic'?' or 'Please spell'strawberry', and the AI will use these tools to give accurate answers.

Applicable scenarios

1. Education and learning: Help students check spelling and count letter frequencies. 2. Word games: Solve word puzzles, detect palindromes, and compare words. 3. Text analysis: Analyze sentence structure and count the number of occurrences of specific characters. 4. Programming assistance: Handle string operations and verify text data. 5. Language learning: Analyze word composition and compare different texts.

Main features

Letter counting
Accurately count the number of occurrences of a specific letter in a word or text. For example, accurately determine that there is only 1 'r' in 'garlic' instead of 2.
Batch counting
Count the number of occurrences of multiple letters simultaneously and obtain a complete letter frequency distribution at once.
Word spelling
Break a word into individual characters to help AI'see' each letter. For example, display'strawberry' as s - t - r - a - w - b - e - r - r - y.
Text analysis
Analyze sentence structure and provide a detailed breakdown at the word level, including the length and character composition of each word.
Palindrome detection
Reverse the text and detect whether it is a palindrome (a word or sentence that reads the same forwards and backwards).
Text comparison
Compare the differences between two texts, including length comparison and character - level contrast.
Tricky word library
Provide a list of common tricky words (e.g.,'strawberry', 'garlic') to help AI avoid errors caused by word segmentation.
Batch operations
Perform statistical operations on multiple words simultaneously to improve processing efficiency.
Advantages
Solve the AI word segmentation problem: Enable large language models to accurately handle individual characters.
High precision: Provide accurate character - level analysis and avoid statistical errors.
Ease of use: No programming knowledge is required, and it can be used through natural language.
Comprehensive functions: More than 14 tools cover most character analysis needs.
Seamless integration: Perfectly integrate with AI assistants such as Claude for a smooth user experience.
Limitations
Dependent on the MCP protocol: It can only be used with AI applications that support MCP.
Limited to text analysis: Focuses on character and text analysis and does not involve semantic understanding.
Requires installation and configuration: Simple installation steps are required for the first use.
Limited in processing long texts: May have limited performance for extremely long texts.

How to use

Install the tool
Install quickly via npx (recommended) or compile and install from the source code.
Configure Claude Desktop
Add MCP server settings to the Claude Desktop configuration file.
Restart the application
Restart Claude Desktop for the configuration to take effect.
Start using
Directly ask character - related questions in the conversation, and the AI will automatically use the tools.

Usage examples

Solve letter - counting disputes
When the AI incorrectly thinks there are 2 'r's in 'garlic', use the count_letter tool to provide an accurate answer.
Word spelling teaching
Help users learn how to correctly spell complex words.
Text comparison analysis
Compare the differences between two similar words.
Palindrome detection game
Detect whether a word or sentence is a palindrome.
Sentence structure analysis
Analyze the word composition of an English sentence.

Frequently Asked Questions

Why does AI need this tool? Can't it count letters by itself?
Does this tool support Chinese or other languages?
Do I need programming knowledge to use it?
Will this tool affect other functions of the AI?
Can it be used in other AI applications besides Claude?
How can I know if the tool is working properly after installation?

Related resources

GitHub repository
Project source code, issue feedback, and contribution guidelines
Complete tool examples
Complete input - output examples of all more than 14 tools
Model Context Protocol official website
Official documentation and specifications of the MCP protocol
Claude Desktop download
AI desktop application supporting MCP
npm package page
npm release page of the toolset

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "char-tools": {
      "command": "npx",
      "args": ["mcp-character-tools"]
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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