diff --git a/docs/gns3-copilot/llm-model-configs-api.md b/docs/gns3-copilot/llm-model-configs-api.md
index 8538164bf..95a122764 100644
--- a/docs/gns3-copilot/llm-model-configs-api.md
+++ b/docs/gns3-copilot/llm-model-configs-api.md
@@ -816,11 +816,6 @@ The `context_limit` value is specified in **K tokens** (thousands of tokens) to
    GPT-4o: 128,000 tokens / 1000 = 128
    ```
 
-3. **Use the reference tool**:
-   ```bash
-   python scripts/show_model_context_limits.py
-   ```
-
 ### Example: Common Models
 
 | Model | Official Value | Configuration |
diff --git a/scripts/show_model_context_limits.py b/scripts/show_model_context_limits.py
deleted file mode 100644
index f07475e4a..000000000
--- a/scripts/show_model_context_limits.py
+++ /dev/null
@@ -1,157 +0,0 @@
-#!/usr/bin/env python3
-"""
-Reference tool for LLM model context limits.
-
-This script provides reference context limit values for common LLM models.
-It helps users find the correct context_limit value when creating LLM model configurations.
-
-IMPORTANT:
-- context_limit unit is K tokens (1 K = 1000 tokens)
-- This tool only displays reference values. You MUST manually configure
-  context_limit when creating or updating LLM model configurations via API.
-
-Usage:
-    python scripts/show_model_context_limits.py
-
-For official documentation, always check:
-- OpenAI: https://platform.openai.com/docs/models
-- Anthropic: https://docs.anthropic.com/claude/docs/models-overview
-- Google: https://ai.google.dev/gemini-api/docs/models
-- DeepSeek: https://platform.deepseek.com/api-docs/
-"""
-
-import sys
-from pathlib import Path
-
-# Add parent directory to path
-sys.path.insert(0, str(Path(__file__).parent.parent))
-
-
-# Reference context limits (as of 2025)
-# Displayed in K tokens for easier configuration
-# Users should verify from official provider documentation
-MODEL_CONTEXT_LIMITS_K = {
-    # OpenAI Models
-    "gpt-4o": 128,
-    "gpt-4o-mini": 128,
-    "gpt-4-turbo": 128,
-    "gpt-4": 8,
-    "gpt-4-32k": 33,
-    "gpt-3.5-turbo": 17,
-    "gpt-3.5-turbo-16k": 17,
-
-    # Anthropic Models
-    "claude-3-5-sonnet-20241022": 200,
-    "claude-3-5-sonnet-20240620": 200,
-    "claude-3-opus-20240229": 200,
-    "claude-3-sonnet-20240229": 200,
-    "claude-3-haiku-20240307": 200,
-
-    # Google Models
-    "gemini-2.0-flash-exp": 1000,
-    "gemini-1.5-pro": 2800,
-    "gemini-1.5-flash": 2800,
-    "gemini-pro": 92,
-
-    # DeepSeek Models
-    "deepseek-chat": 128,
-    "deepseek-coder": 128,
-
-    # xAI Models
-    "grok-beta": 128,
-}
-
-
-def find_context_limit_for_model(model_name: str) -> int | None:
-    """Find the context limit for a given model name (in K tokens)."""
-    model_lower = model_name.lower().strip()
-
-    # Try exact match
-    if model_lower in MODEL_CONTEXT_LIMITS_K:
-        return MODEL_CONTEXT_LIMITS_K[model_lower]
-
-    # Try prefix match
-    for key, limit in MODEL_CONTEXT_LIMITS_K.items():
-        if model_lower.startswith(key.lower()):
-            return limit
-
-    return None
-
-
-def main():
-    print("=" * 70)
-    print("LLM Model Context Limits Reference Tool")
-    print("=" * 70)
-    print()
-    print("This tool displays reference context limit values for common LLM models.")
-    print("Please verify from official provider documentation before configuring.")
-    print()
-    print("IMPORTANT: context_limit unit is K tokens (1 K = 1,000 tokens)")
-    print()
-    print("Official Documentation:")
-    print("  - OpenAI: https://platform.openai.com/docs/models")
-    print("  - Anthropic: https://docs.anthropic.com/claude/docs/models-overview")
-    print("  - Google: https://ai.google.dev/gemini-api/docs/models")
-    print("  - DeepSeek: https://platform.deepseek.com/api-docs/")
-    print()
-
-    # Display all reference values
-    print("=" * 70)
-    print("Reference Context Limits (in K tokens)")
-    print("=" * 70)
-    print()
-
-    # Group by provider
-    providers = {
-        "OpenAI": ["gpt-4o", "gpt-4o-mini", "gpt-4-turbo", "gpt-4", "gpt-4-32k", "gpt-3.5-turbo", "gpt-3.5-turbo-16k"],
-        "Anthropic": ["claude-3-5-sonnet-20241022", "claude-3-5-sonnet-20240620", "claude-3-opus-20240229", "claude-3-sonnet-20240229", "claude-3-haiku-20240307"],
-        "Google": ["gemini-2.0-flash-exp", "gemini-1.5-pro", "gemini-1.5-flash", "gemini-pro"],
-        "DeepSeek": ["deepseek-chat", "deepseek-coder"],
-        "xAI": ["grok-beta"],
-    }
-
-    for provider, models in providers.items():
-        print(f"\n{provider}:")
-        for model in models:
-            if model in MODEL_CONTEXT_LIMITS_K:
-                limit_k = MODEL_CONTEXT_LIMITS_K[model]
-                limit_actual = limit_k * 1000
-                print(f"  {model:40s} → {limit_k:4d}K (= {limit_actual:,} tokens)")
-
-    print()
-    print("=" * 70)
-    print()
-    print("Conversion Examples:")
-    print()
-    print("  Official Documentation: 128,000 tokens")
-    print("  ↓")
-    print("  API Configuration: \"context_limit\": 128")
-    print()
-    print("  Official Documentation: 200,000 tokens")
-    print("  ↓")
-    print("  API Configuration: \"context_limit\": 200")
-    print()
-    print("  Official Documentation: 2,800,000 tokens")
-    print("  ↓")
-    print("  API Configuration: \"context_limit\": 2800")
-    print()
-    print("=" * 70)
-    print()
-    print("Usage Example:")
-    print()
-    print("When creating a model configuration, specify context_limit in K:")
-    print()
-    print('  POST /v3/users/{user_id}/llm-model-configs')
-    print('  {')
-    print('    "name": "GPT-4o Configuration",')
-    print('    "provider": "openai",')
-    print('    "model": "gpt-4o",')
-    print('    "context_limit": 128,  // ← Required: 128K = 128,000 tokens')
-    print('    "context_strategy": "balanced"')
-    print('  }')
-    print()
-    print("=" * 70)
-
-
-if __name__ == "__main__":
-    main()