# Token Count Estimator AI Agent Connect

> Deterministic LLM token estimation using character-based heuristics.

## Overview
- **Category:** developer-tools
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_WRXaDwN8B6yoUlZJBByOQGcYopoEFZ1yRxVUQweP/ai-agent-connect
- **Tags:** tokens, llm, gpt-4, claude, estimation

## Description

This MCP server provides precise, deterministic estimation of LLM input sizes. By using model-specific linguistic ratios and structural density analysis, it calculates token counts for various architectures including GPT-4, Claude, Llama, and Gemma. Use `estimate_token_usage` to get a full breakdown of words, punctuation, and whitespace, or `analyze_text_complexity` to detect code and URL density. It also provides a confidence interval and warns when you are approaching the context window limit.

## Tools

### analyze_text_complexity
Evaluates the structural characteristics of the text to prepare for specialized density calculations

### estimate_token_usage
Provides a comprehensive breakdown of the estimated token count and remaining capacity for a given input

### get_model_ratios
Retrieves the hardcoded character-to-token ratios for the specific model and language requested

## Prompt Examples

**Prompt:** 
```
Estimate the token usage for this text: 'Hello, world!' using gpt-4 in english with a 4096 context window.
```

**Response:** 
```
The estimated token count is 3 tokens, with 4093 tokens remaining in the context window.
```

**Prompt:** 
```
Analyze the complexity of this code snippet: 'def add(a, b): return a + b'
```

**Response:** 
```
The text is identified as code with 1 detected numeric sequence and 0 URLs.
```

**Prompt:** 
```
What is the character-to-token ratio for Claude in Chinese?
```

**Response:** 
```
The character-to-token ratio for Claude in Chinese is 1.2.
```

## Frequently Asked Questions

**How accurate are these token estimates?**
The estimates use deterministic character-based heuristics. For English, we provide a ±10% confidence interval, while mixed languages use a ±15% interval.

**Which models are supported?**
The server supports GPT-4, Claude, Llama, and Gemma through specific character-to-token ratios.

**Can I detect if my text is too long for the model?**
Yes, the `estimate_token_usage` tool includes an `isOverCapacityWarning` flag that triggers when you exceed 90% of the specified context window.