MCP Character Tools

You have MCP Character Tools, a server that provides 14+ character and text analysis utilities to help large language models work with individual characters and counts. It makes character-level operations reliable for tasks like counting specific letters, computing frequencies, breaking words into characters, and more. This MCP server helps you gain precise character-level insight that tokenization can miss, enabling more accurate analysis and prompting workflows.

How to use

Install and run the MCP Character Tools server, then connect your MCP client to perform character- and text-focused analyses. You can interact with the suite of tools to count letters, find substrings, get character at specific positions, reverse text, compare texts, and perform word-by-word analyses. The server exposes a set of tools that you can invoke from your MCP client to process text inputs and retrieve structured results.

How to install

Prerequisites: Node.js (including npm) should be installed on your system.

# Via npx (recommended)
npx mcp-character-tools

# Via npm (global install)
npm install -g mcp-character-tools
mcp-character-tools

# From source
git clone https://github.com/Aaryan-Kapoor/mcp-character-tools
cd mcp-character-tools
npm install
npm run build
npm start

Additional sections

Configuration notes for connecting from your MCP client are provided below. If you are using Claude Desktop, you can add the server to your configuration with the appropriate command and arguments as shown in examples.

Available tools

count_letter

Count a specific letter in the input text.

count_letters

Count multiple letters at once in the input text.

count_substring

Count occurrences of a substring within the text.

letter_frequency

Compute the frequency distribution of letters in the text.

spell_word

Break text into its individual characters.

char_at

Return the character at a given index.

nth_character

Get the nth character of a string (1-based).

word_length

Return the exact length of the input text.

reverse_text

Reverse the text and detect palindromes.

compare_texts

Compare two texts and report differences.

analyze_sentence

Provide a word-by-word breakdown of a sentence.

batch_count

Count across multiple input words in one pass.

get_tricky_words

List words commonly miscounted and why.

check_tricky_word

Determine if a given word is tricky to count or analyze.