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# /////////////////////////////////////////////
# Xyizko - MCH Hackathon 2025 Skeleton
# x.com/xyizko
# /////////////////////////////////////////////
# --- Imports Section ---
import datetime
import gradio as gr
# Importing Smolagents with error handling
try:
from smolagents import CodeAgent, HfApiModel
SMOLAGENTS_AVAILABLE = True
except ImportError:
SMOLAGENTS_AVAILABLE = False
print("β οΈ SmolAgents not available, using direct HF API")
# Fallback to HuggingFace Hub
from huggingface_hub import InferenceClient
# --- Demo UI Component Functions ---
# App Introduction Function
def demo_vid():
gr.Markdown("# Video Demo")
gr.HTML("""
<iframe width="560" height="315"
src="https://www.youtube.com/embed/Ttj49yTI46w?si=1FZeoSNivLxozQy0"
title="YouTube video player"
frameborder="0"
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
referrerpolicy="strict-origin-when-cross-origin"
allowfullscreen>
</iframe>
""")
def app_intro():
intro_text = """
# π€ Xyizko - MCP Hackathon 2025 Submission - Web3-Security-Auditor
1. This is a submission for the Gradio MCP Hackathon Project.
2. This submision is for **Track 1 (MCP Tool / Server)** and **Track3 (Agentic Demo Showcase)**
3. https://huggingface.co/Agents-MCP-Hackathon - Official Hackathon Announcement.
4. Project is both Agentic and a MCP Server uisng HugginFace an Gradio Libraries.
# βοΈ App Description
**AI-Powered Smart Contract Security Analysis Platform**
1. This tool leverages AI to analyze smart contracts for vulnerabilities,
anti-patterns, and security issues. Upload your contract code and get comprehensive
security analysis powered by Hugging Face models.
2. https://github.com/RareSkills/Buggy-ERC-20 - Test Buggy ERC-20 Contracts Source
"""
ai_system_info = f"""
## π€ AI Analysis System
**SmolAgents Status**: {'β
Available' if SMOLAGENTS_AVAILABLE else 'β Not Available - Using Direct HF API'}
### What Our AI System Does:
#### π§ **Intelligent Code Analysis**
{'- SmolAgents CodeAgent for specialized code analysis' if SMOLAGENTS_AVAILABLE else '- Direct HuggingFace Inference API calls'}
- Multi-step security vulnerability detection
- Risk assessment and scoring
- Code quality evaluation
- Actionable security recommendations
#### π― **Analysis Capabilities**
1. **Security Vulnerability Detection**: Identifies reentrancy, overflow, access control issues
2. **Risk Assessment**: Intelligent risk scoring and prioritization
3. **Code Quality Analysis**: Best practices and optimization evaluation
4. **Pattern Recognition**: Detects anti-patterns and security smells
5. **Actionable Recommendations**: Generates specific improvement suggestions
#### π **System Features**
- **Reliable**: Robust error handling with fallback mechanisms
- **Flexible**: Works with various HuggingFace models
- **Comprehensive**: Multi-dimensional analysis approach
- **Practical**: Provides actionable, implementable recommendations
"""
# NEW MCP Integration Info
mcp_integration_info = """
## π Model Context Protocol (MCP) Integration
**π This app is now MCP-enabled!** AI assistants like Claude can use it as a specialized security tool.
### π οΈ Available MCP Tool:
#### π‘οΈ `analyze_smart_contract`
- **Purpose**: Complete smart contract security analysis
- **Features**: Security vulnerabilities + Risk scoring + Code quality assessment
- **AI-Powered**: Uses HuggingFace models with intelligent rule-based fallback
- **Input**: Just paste your Solidity contract code
- **Output**: Comprehensive security report with actionable recommendations
- **Reliability**: Always works - even without API tokens (fallback analysis)
### π€ How AI Assistants Use This:
**Claude Desktop Integration:**
```json
{
"mcpServers": {
"smart-contract-analyzer": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-gradio", "YOUR_HF_SPACE_URL"]
}
}
}
```
**Example AI Conversation:**
```
User: "Analyze this smart contract for security issues: [paste contract]"
Claude: [Uses analyze_smart_contract tool]
"I've analyzed your contract and found 3 critical vulnerabilities..."
```
### β¨ Key Benefits:
- **One-Click Security**: AI assistants can instantly analyze any contract
- **Always Available**: Hosted on reliable HuggingFace infrastructure
- **No Setup Required**: AI assistants connect directly to your public space
- **Professional Reports**: Detailed analysis with specific remediation steps
"""
part3 = """
## Development Progress
> Changelog - Fri Jun 6 08:14:02 PM UTC 2025
1. β
Implement robust AI analysis system
2. β
SmolAgents integration with proper error handling
3. β
Direct HF API fallback for maximum compatibility
4. β
Enhanced analysis with multiple approaches
5. β
Comprehensive security assessment capabilities
6. β
**NEW: Model Context Protocol (MCP) Integration**
7. β
**NEW: Single powerful MCP tool for AI assistants**
8. β
**NEW: Lightweight deployment (no transformers/torch dependencies)**
9. β
**NEW: Proper Gradio MCP server setup with mcp_server=True**
### About Author
1. X - https://x.com/xyizko
2. Project Acknowledgements - https://x.com/Gradio/status/1930951866935910753
"""
gr.Markdown(intro_text)
gr.Markdown(ai_system_info)
gr.Markdown(mcp_integration_info)
gr.Markdown(
value="""
```mermaid
flowchart LR
A[Smart Contract Code] -->|Upload/MCP| B{AI Analysis System}
B -->|SmolAgents Available| C[CodeAgent Analysis]
B -->|Fallback| D[Direct HF API]
C --> E[Multi-Step Analysis]
D --> E
E --> F[Security Assessment]
E --> G[Risk Scoring]
E --> H[Quality Review]
F --> I[Comprehensive Report]
G --> I
H --> I
I --> J[Gradio UI Output]
I --> K[MCP Tool Response]
K --> L[AI Assistant Integration]
J --> M[Downloadable Analysis]
```
""")
gr.Markdown(part3)
# --- Smart Contract Agent ---
def create_smart_contract_analyzer(hf_token, model_name):
"""Create AI analyzer using SmolAgents or direct HF API"""
if SMOLAGENTS_AVAILABLE:
try:
model = HfApiModel(model_id=model_name, token=hf_token)
agent = CodeAgent(tools=[], model=model)
return {"type": "smolagent", "instance": agent, "model": model_name}
except Exception as e:
print(f"SmolAgents creation failed: {e}")
try:
client = InferenceClient(token=hf_token)
test_response = client.text_generation(
prompt="Test prompt",
model=model_name,
max_new_tokens=5
)
return {"type": "direct_api", "instance": client, "model": model_name}
except Exception as e:
raise Exception(f"Failed to create AI analyzer: {str(e)}")
def run_ai_analysis(analyzer, contract_code, analysis_type):
"""Run AI analysis using available method"""
prompts = {
"security": f"""Analyze this Solidity smart contract for security vulnerabilities:
```solidity
{contract_code[:3000]}
```
Identify:
1. Security vulnerabilities (reentrancy, overflow, access control)
2. Risk level for each issue (Critical/High/Medium/Low)
3. Specific remediation steps
Be concise and practical.""",
"risk": f"""Assess the risk level of this smart contract (scale 1-10):
```solidity
{contract_code[:3000]}
```
Provide:
1. Overall risk score (1-10)
2. Main risk factors
3. Top 3 recommendations
Be specific and actionable.""",
"quality": f"""Review the code quality of this smart contract:
```solidity
{contract_code[:3000]}
```
Evaluate:
1. Solidity best practices
2. Gas optimization opportunities
3. Code organization
Provide specific improvement suggestions."""
}
prompt = prompts.get(analysis_type, prompts["security"])
try:
if analyzer["type"] == "smolagent":
result = analyzer["instance"].run(prompt)
return str(result)
else:
response = analyzer["instance"].text_generation(
prompt=prompt,
model=analyzer["model"],
max_new_tokens=600,
temperature=0.5,
do_sample=True
)
if isinstance(response, str):
return response.strip()
elif hasattr(response, 'generated_text'):
return response.generated_text.strip()
else:
return str(response)
except Exception as e:
error_msg = str(e).lower()
if "not found" in error_msg or "404" in error_msg:
return f"β Model '{analyzer.get('model', 'unknown')}' not found. Try: microsoft/DialoGPT-medium"
elif "unauthorized" in error_msg or "403" in error_msg:
return "β Invalid API token or insufficient permissions"
elif "rate limit" in error_msg:
return "β Rate limit exceeded. Please wait and try again"
else:
return f"β Analysis failed: {str(e)}"
def enhanced_fallback_analysis(content, analysis_type):
"""Comprehensive fallback analysis when AI fails"""
lines = content.splitlines()
functions = content.count('function')
if analysis_type == "security":
vulnerabilities = []
risk_score = 0
if 'call.value' in content or '.call(' in content:
vulnerabilities.append(
"π΄ **CRITICAL**: Potential reentrancy vulnerability (call.value/.call usage)")
risk_score += 4
if 'tx.origin' in content:
vulnerabilities.append(
"π‘ **MEDIUM**: Authentication bypass risk (tx.origin usage)")
risk_score += 2
if 'block.timestamp' in content or 'now' in content:
vulnerabilities.append("π‘ **MEDIUM**: Timestamp manipulation risk")
risk_score += 1
if not any(word in content.lower() for word in ['require', 'assert', 'revert']):
vulnerabilities.append("π **HIGH**: Missing input validation")
risk_score += 3
if 'selfdestruct' in content:
vulnerabilities.append(
"π΄ **CRITICAL**: Contract can be destroyed (selfdestruct)")
risk_score += 4
if 'delegatecall' in content:
vulnerabilities.append("π **HIGH**: Dangerous delegate call usage")
risk_score += 3
if functions > 20:
vulnerabilities.append(
"π‘ **MEDIUM**: High complexity (many functions)")
risk_score += 1
return f"""**Security Analysis Results:**
**Vulnerabilities Found:** {len(vulnerabilities)}
**Risk Score:** {min(risk_score, 10)}/10
{chr(10).join(vulnerabilities) if vulnerabilities else "β
No major vulnerabilities detected in static analysis"}
**Recommendations:**
- Implement reentrancy guards for external calls
- Use msg.sender instead of tx.origin
- Add comprehensive input validation
- Consider formal verification for critical functions"""
elif analysis_type == "risk":
risk_factors = []
score = 0
if 'call.value' in content:
score += 3
risk_factors.append("External call risks")
if len(lines) > 500:
score += 1
risk_factors.append("Large codebase")
if functions > 15:
score += 1
risk_factors.append("High complexity")
if 'owner' in content.lower():
score += 1
risk_factors.append("Centralized control")
if content.count('mapping') > 5:
score += 1
risk_factors.append("Complex state")
risk_level = "Critical" if score >= 6 else "High" if score >= 4 else "Medium" if score >= 2 else "Low"
return f"""**Risk Assessment:**
**Overall Risk Score:** {score}/10
**Risk Level:** {risk_level}
**Risk Factors:**
{chr(10).join([f"- {factor}" for factor in risk_factors]) if risk_factors else "- Minimal risk factors identified"}
**Priority Actions:**
1. {"Immediate security review required" if score >= 4 else "Standard review recommended"}
2. {"Implement emergency pause mechanism" if score >= 6 else "Add comprehensive testing"}
3. {"Consider professional audit" if score >= 3 else "Document all functions"}"""
elif analysis_type == "quality":
quality_issues = []
score = 100
if content.count('pragma') == 0:
quality_issues.append("β Missing pragma statement (-10 points)")
score -= 10
if content.count('//') < functions / 2:
quality_issues.append("β οΈ Insufficient documentation (-15 points)")
score -= 15
if len(lines) > 1000:
quality_issues.append(
"β οΈ Contract too large, consider splitting (-10 points)")
score -= 10
if 'TODO' in content or 'FIXME' in content:
quality_issues.append(
"β οΈ Unfinished code markers found (-5 points)")
score -= 5
if not any(modifier in content for modifier in ['public', 'private', 'internal', 'external']):
quality_issues.append(
"β Missing function visibility specifiers (-20 points)")
score -= 20
return f"""**Code Quality Assessment:**
**Quality Score:** {max(score, 0)}/100
**Issues Found:**
{chr(10).join(quality_issues) if quality_issues else "β
No major quality issues detected"}
**Improvement Suggestions:**
- Add comprehensive NatSpec documentation
- Implement consistent naming conventions
- Use latest Solidity version with appropriate pragma
- Add function visibility specifiers
- Consider gas optimization patterns"""
# --- MCP Tool Function ---
def analyze_smart_contract(contract_code: str, hf_token: str = "", hf_model: str = "microsoft/DialoGPT-medium"):
"""
MCP Tool: Comprehensive smart contract security analysis
This function will be automatically exposed as an MCP tool when mcp_server=True
Args:
contract_code: Solidity smart contract source code
hf_token: Optional HuggingFace API token for AI analysis
hf_model: HuggingFace model name (default: microsoft/DialoGPT-medium)
Returns:
Complete security analysis report with vulnerabilities, risk assessment, and recommendations
"""
try:
# Initialize analyzer if token provided
analyzer = None
analysis_method = "Enhanced Rule-Based Fallback"
if hf_token.strip():
try:
analyzer = create_smart_contract_analyzer(hf_token, hf_model)
analysis_method = f"AI-Powered ({analyzer['type']})"
except Exception as e:
# Continue with fallback analysis
analysis_method = f"Rule-Based Fallback (AI failed: {str(e)[:50]}...)"
# Perform comprehensive analysis
if analyzer:
# Try AI analysis first
security_result = run_ai_analysis(
analyzer, contract_code, "security")
if security_result.startswith("β"):
security_result = enhanced_fallback_analysis(
contract_code, "security")
risk_result = run_ai_analysis(analyzer, contract_code, "risk")
if risk_result.startswith("β"):
risk_result = enhanced_fallback_analysis(contract_code, "risk")
quality_result = run_ai_analysis(
analyzer, contract_code, "quality")
if quality_result.startswith("β"):
quality_result = enhanced_fallback_analysis(
contract_code, "quality")
else:
# Use enhanced fallback analysis
security_result = enhanced_fallback_analysis(
contract_code, "security")
risk_result = enhanced_fallback_analysis(contract_code, "risk")
quality_result = enhanced_fallback_analysis(
contract_code, "quality")
# Contract statistics
lines = contract_code.splitlines()
function_count = contract_code.count('function')
modifier_count = contract_code.count('modifier')
pragma_count = contract_code.count('pragma')
# Generate comprehensive report
report = f"""# π‘οΈ Smart Contract Security Analysis Report
## π Analysis Overview
**Analysis Method**: {analysis_method}
**Model Used**: {hf_model if analyzer else 'Rule-Based Analysis Engine'}
**Timestamp**: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S UTC')}
**Analysis Tool**: Xyizko Smart Contract Analyzer (MCP-Enabled)
## π Contract Metrics
- **Lines of Code**: {len(lines)}
- **Functions**: {function_count}
- **Modifiers**: {modifier_count}
- **Pragma Statements**: {pragma_count}
- **Code Size**: {len(contract_code)} characters
## π‘οΈ Security Vulnerability Assessment
{security_result}
## π― Risk Assessment & Scoring
{risk_result}
## π Code Quality Analysis
{quality_result}
## π Executive Summary & Recommendations
### π¨ Immediate Actions Required:
- Review and address any CRITICAL or HIGH severity vulnerabilities
- Implement recommended security improvements
- Add missing input validations and access controls
### π§ Development Best Practices:
- Follow Solidity security patterns and conventions
- Implement comprehensive testing including edge cases
- Consider formal verification for critical functions
### ποΈ Deployment Readiness:
- {"β οΈ NOT READY: Address critical issues before deployment" if "CRITICAL" in security_result else "β
Ready for thorough testing and audit review"}
- Professional security audit recommended before mainnet deployment
- Implement emergency pause mechanisms for production contracts
---
**Analysis powered by Xyizko Smart Contract Analyzer**
*MCP-enabled AI tool for comprehensive smart contract security assessment*
"""
return report
except Exception as e:
return f"""# β Smart Contract Analysis Failed
**Error**: {str(e)}
**Timestamp**: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S UTC')}
## Troubleshooting:
- Ensure contract code is valid Solidity
- Check HuggingFace token if using AI analysis
- Try with a different model name
- Contact support if the issue persists
---
*Xyizko Smart Contract Analyzer - MCP Tool*
"""
# --- Smart Contract Analysis Tab ---
def upload_tab():
system_status = "SmolAgents + HF API" if SMOLAGENTS_AVAILABLE else "Direct HF API"
upload_description = f"""
# Smart Contract AI Analysis
> Upload your smart contract and get comprehensive AI-powered security analysis.
**Current System**: {system_status}
## How it works:
1. **Upload**: Select your smart contract (.txt, .sol files)
2. **Configure**: Enter your Hugging Face API token and model
3. **AI Analysis**: {'SmolAgents or' if SMOLAGENTS_AVAILABLE else ''} Direct API analysis with fallback
4. **Download**: Get detailed analysis reports with actionable recommendations
"""
analysis_info = """
## Analysis Features
- **π‘οΈ Security Analysis**: Comprehensive vulnerability detection
- **π― Risk Assessment**: Intelligent risk scoring (1-10 scale)
- **π Code Quality Review**: Best practices evaluation
- **π§ Fallback Analysis**: Robust rule-based analysis when AI fails
- **π Actionable Reports**: Specific, implementable recommendations
## Recommended Models
- **Qwen/Qwen3-235B-A22B**
- **mistralai/Mistral-7B-Instruct-v0.3**
- **google/flan-t5-base**
- **meta-llama/Llama-3.3-70B-Instruct**
- Note premium and frontier models provide the highest quality
"""
def analyze_contract_ui(file, hf_token, hf_model, progress=gr.Progress()):
if file is None:
return "β No file uploaded.", "", gr.update(visible=False)
if not hf_token.strip():
return "β Please provide a valid Hugging Face API token.", "", gr.update(visible=False)
if not hf_model.strip():
return "β Please specify a Hugging Face model name.", "", gr.update(visible=False)
try:
progress(0.1, desc="π Reading contract file...")
# Read file content
if hasattr(file, 'read'):
content = file.read().decode("utf-8")
else:
with open(file.name, 'r', encoding='utf-8') as f:
content = f.read()
# Limit content size
if len(content) > 10000:
content = content[:10000] + "\n// ... (truncated for analysis)"
progress(0.3, desc="π€ Running comprehensive analysis...")
# Use the MCP function for consistency
analysis_result = analyze_smart_contract(
content, hf_token, hf_model)
progress(0.9, desc="πΎ Creating downloadable report...")
# Create downloadable report
timestamp = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
report_content = f"""# Smart Contract Security Analysis Report
**Generated by**: Xyizko Smart Contract Analyzer
**Date**: {datetime.datetime.now().strftime("%Y-%m-%d at %H:%M:%S")}
{analysis_result}
---
*Report generated by Xyizko Smart Contract Analyzer - MCH Hackathon 2025*
"""
progress(1.0, desc="β
Analysis complete!")
# Create downloadable file
report_filename = f"contract_analysis_{timestamp}.md"
try:
with open(report_filename, 'w', encoding='utf-8') as f:
f.write(report_content)
return (
"β
Analysis completed successfully!",
analysis_result,
gr.update(visible=True, value=report_filename)
)
except Exception:
return (
"β
Analysis completed! (Download creation failed)",
analysis_result,
gr.update(visible=False)
)
except Exception as e:
return f"β Analysis error: {str(e)}", "", gr.update(visible=False)
with gr.Column():
gr.Markdown(upload_description)
gr.Markdown(analysis_info)
with gr.Row():
with gr.Column(scale=2):
file_input = gr.File(
label="π Upload Smart Contract",
file_types=[".txt", ".sol"],
height=120
)
hf_token_input = gr.Textbox(
label="π Hugging Face API Token",
placeholder="hf_xxxxxxxxxxxxxxxxxxxxxxxxx",
type="password",
info="Get your token from https://huggingface.co/settings/tokens"
)
hf_model_input = gr.Textbox(
label="π€ Hugging Face Model",
placeholder="microsoft/DialoGPT-medium",
value="microsoft/DialoGPT-medium",
info="Recommended: microsoft/DialoGPT-medium (Lightweight & Reliable)"
)
with gr.Column(scale=1):
analyze_btn = gr.Button(
"π Start Analysis",
variant="primary",
size="lg",
scale=2
)
gr.Markdown("---")
status_output = gr.Textbox(
label="π Analysis Status",
lines=2,
interactive=False,
show_copy_button=True
)
analysis_output = gr.Textbox(
label="π Analysis Results",
lines=20,
max_lines=25,
show_copy_button=True
)
download_file = gr.File(
label="π₯ Download Analysis Report (Markdown)",
visible=False
)
analyze_btn.click(
fn=analyze_contract_ui,
inputs=[file_input, hf_token_input, hf_model_input],
outputs=[status_output, analysis_output, download_file]
)
# --- MCP Integration Tab ---
def mcp_integration_tab():
"""Simple MCP Integration and Testing Tab"""
mcp_info = """
# π MCP Integration - One Powerful Tool
This Smart Contract Analyzer provides **one comprehensive MCP tool** that AI assistants can use.
## π‘οΈ `analyze_smart_contract` - The Complete Security Tool
**What it does:**
- β
**Security Vulnerability Detection** (reentrancy, access control, etc.)
- β
**Risk Assessment & Scoring** (1-10 scale with detailed factors)
- β
**Code Quality Analysis** (best practices, optimization opportunities)
- β
**Actionable Recommendations** (specific steps to fix issues)
- β
**Always Works** (AI-powered with intelligent fallback)
**Parameters:**
- `contract_code` (required): Your Solidity smart contract code
- `hf_token` (optional): HuggingFace API token for AI analysis
- `hf_model` (optional): Model name (default: microsoft/DialoGPT-medium)
## π For AI Assistants (Claude, etc.):
**Claude Desktop Config:**
```json
{
"mcpServers": {
"smart-contract-analyzer": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-gradio", "YOUR_HF_SPACE_URL"]
}
}
}
```
**Example Usage:**
```
"Analyze this smart contract for security issues:
pragma solidity ^0.8.0;
contract MyContract {
// Your contract code here
}"
```
**Benefits:**
- π― **Simple**: One tool does everything
- π‘οΈ **Reliable**: Always works (even without API tokens)
- π **Fast**: Lightweight dependencies
- π **Comprehensive**: Complete security assessment
"""
def test_mcp_tool(contract_code, hf_token, hf_model):
"""Test the MCP tool directly"""
if not contract_code.strip():
return "β Please provide contract code to test the MCP tool"
try:
result = analyze_smart_contract(contract_code, hf_token, hf_model)
return result
except Exception as e:
return f"β MCP Tool Error: {str(e)}"
def generate_claude_config(hf_space_url):
"""Generate Claude Desktop configuration"""
if not hf_space_url.strip():
hf_space_url = "https://your-username-smart-contract-analyzer.hf.space"
config = f'''{{\n "mcpServers": {{\n "smart-contract-analyzer": {{\n "command": "npx",\n "args": [\n "-y", \n "@modelcontextprotocol/server-gradio",\n "{hf_space_url}"\n ]\n }}\n }}\n}}'''
return config
with gr.Column():
gr.Markdown(mcp_info)
gr.Markdown("## π§ͺ Test the MCP Tool")
with gr.Row():
with gr.Column(scale=2):
test_contract = gr.Textbox(
label="π Contract Code",
placeholder="""pragma solidity ^0.8.0;
contract TestContract {
address owner;
mapping(address => uint) balances;
function withdraw() public {
uint amount = balances[msg.sender];
(bool success, ) = msg.sender.call{value: amount}("");
balances[msg.sender] = 0;
}
}""",
lines=12
)
test_token = gr.Textbox(
label="π HF Token (Optional)",
placeholder="hf_xxxxxxxxx (leave empty for rule-based analysis)",
type="password"
)
test_model = gr.Textbox(
label="π€ Model (Optional)",
placeholder="microsoft/DialoGPT-medium",
value="microsoft/DialoGPT-medium"
)
with gr.Column(scale=1):
test_btn = gr.Button(
"π§ͺ Test MCP Tool",
variant="primary",
size="lg"
)
gr.Markdown("### π Generate Config")
space_url = gr.Textbox(
label="π Your HF Space URL",
placeholder="https://your-space.hf.space"
)
config_btn = gr.Button(
"π Generate Claude Config",
variant="secondary"
)
test_output = gr.Textbox(
label="π MCP Tool Test Results",
lines=25,
show_copy_button=True
)
claude_config = gr.Textbox(
label="π Claude Desktop Configuration",
lines=12,
show_copy_button=True
)
test_btn.click(
fn=test_mcp_tool,
inputs=[test_contract, test_token, test_model],
outputs=[test_output]
)
config_btn.click(
fn=generate_claude_config,
inputs=[space_url],
outputs=[claude_config]
)
# /////////////////////////////////////////////////////////////////////////////////
# --- Main Demo UI Function ---
with gr.Blocks(
theme=gr.themes.Soft(),
title="Xyizko - Smart Contract Analyzer"
) as demo:
with gr.Tab("π Docs"):
demo_vid()
app_intro()
with gr.Tab("π Analyzer Agent"):
upload_tab()
with gr.Tab("π MCP Integration"):
mcp_integration_tab()
if __name__ == "__main__":
print("π Starting Xyizko Smart Contract Analyzer...")
print("π MCP Integration: ENABLED (mcp_server=True)")
print("π€ AI Analysis: SmolAgents + HF API with Fallback")
print("β‘ Lightweight: No transformers/torch dependencies")
print("π‘ Deploy to HuggingFace Spaces for public MCP access!")
demo.launch(
mcp_server=True,
share=False,
server_name="0.0.0.0",
show_error=True
)
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