MCP Character Tools

Count occurrences of a specific letter in text.

Returns the count, positions, a visual breakdown showing where each letter appears, and a density percentage.

Args:

• text (string): The text to analyze

• letter (string): The single letter to count

• case_sensitive (boolean): Whether to match case exactly (default: false)

Returns: count, positions array, visual breakdown, and density summary.

Example: count_letter("strawberry", "r") → count: 3, positions: [2, 5, 8]

Count occurrences of multiple letters at once.

Efficiently counts several letters in a single call.

Args:

• text (string): The text to analyze

• letters (string[]): Array of letters to count

• case_sensitive (boolean): Match case exactly (default: false)

Returns: Results for each letter with counts and positions.

Example: count_letters("strawberry", ["r", "s", "e"]) → r: 3, s: 1, e: 1

Count occurrences of a substring or pattern in text.

Can count overlapping or non-overlapping matches.

Args:

• text (string): The text to search in

• substring (string): The pattern to find

• case_sensitive (boolean): Match case exactly (default: false)

• overlapping (boolean): Count overlapping matches (default: false)

Returns: count and positions of each match.

Example: count_substring("banana", "ana", overlapping=true) → count: 2, positions: [1, 3]

Get frequency distribution of all characters in text.

Provides a complete breakdown of character frequencies.

Args:

• text (string): The text to analyze

• case_sensitive (boolean): Distinguish upper/lowercase (default: false)

• include_spaces (boolean): Include spaces in count (default: false)

• include_punctuation (boolean): Include punctuation (default: false)

• letters_only (boolean): Only count a-z letters (default: true)

Returns: Frequency map, sorted list, most/least common characters.

Example: letter_frequency("hello") → h: 1, e: 1, l: 2, o: 1

Break text into individual characters with optional indices.

Perfect for verifying character-by-character content.

Args:

• text (string): The text to spell out

• include_indices (boolean): Include position numbers (default: true)

Returns: Array of characters, indexed list, spelled out string.

Example: spell_word("cat") → ['c', 'a', 't'] with indices [0:'c', 1:'a', 2:'t']

Get the character at a specific index (0-based). Supports negative indices.

Args:

• text (string): The text to index into

• index (number): Position (0-based, negative counts from end)

Returns: The character at that position, or error if out of bounds.

Example: char_at("hello", 1) → 'e'; char_at("hello", -1) → 'o'

Get the nth character (1-based, human-friendly numbering).

"What's the 3rd letter?" uses position=3.

Args:

• text (string): The text to examine

• position (number): Which character (1 = first, 2 = second, etc.)

• from_end (boolean): Count from end instead (default: false)

Returns: The character and a human-readable description.

Example: nth_character("hello", 2) → 'e' (the 2nd character)

Get the exact length of text with detailed breakdown.

Args:

• text (string): The text to measure

• count_spaces (boolean): Include spaces in length (default: true)

Returns: Total length, length without spaces, space count, word count.

Example: word_length("hello world") → 11 total, 10 without spaces, 2 words

Reverse text character-by-character or word-by-word.

Also detects if the text is a palindrome.

Args:

• text (string): The text to reverse

• reverse_words_only (boolean): Reverse word order only, not characters (default: false)

Returns: Reversed text, palindrome detection.

Example: reverse_text("hello") → "olleh"; reverse_text("racecar") → "racecar" (palindrome!)

Compare letter frequencies between two texts.

Useful for analyzing similarity or differences.

Args:

• text1 (string): First text

• text2 (string): Second text

• case_sensitive (boolean): Distinguish case (default: false)

Returns: Common characters, unique to each, frequency comparison, similarity score.

Example: compare_texts("hello", "world") → common: ['l', 'o'], unique_to_text1: ['h', 'e'], etc.

Analyze a sentence word-by-word for a specific letter.

Shows exactly how many times a letter appears in each word.

Args:

• text (string): The sentence to analyze

• letter (string): The letter to count

• case_sensitive (boolean): Match case exactly (default: false)

Returns: Per-word breakdown with counts and positions.

Example: analyze_sentence("The strawberry was very ripe", "r") → per-word counts

Count a letter across multiple words at once.

Efficiently process a list of words.

Args:

• words (string[]): Array of words to analyze

• letter (string): The letter to count

• case_sensitive (boolean): Match case exactly (default: false)

Returns: Results for each word, totals, sorted by count.

Example: batch_count(["strawberry", "raspberry", "blueberry"], "r") → individual and total counts

Get a list of words that are commonly miscounted by LLMs.

These are words with double letters, repeated patterns, or other features that cause counting errors.

Returns: List of tricky words with correct counts and explanations.

Example: Returns "strawberry" with explanation that it has 3 r's, not 2.

Look up a specific word to see if it's a commonly miscounted word.

Args:

• word (string): The word to check

Returns: Information about common mistakes if it's a tricky word, or empty if not.

Example: check_tricky_word("strawberry") → explains the 3 r's and common mistake of counting 2