HefestoAI
Pre-commit code quality guardian. Detects semantic drift in AI-generated code.
我該用這個嗎
品質與安全性
B
發現項目(1)
- LOW在 compare 中
根據工具定義與協定合規性的自動化分析。
上下文成本
~212Token(工具定義)
~354 B典型回應大小
極小的注意力影響(128k 上下文的 0.17%)
這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高,可用於其他工作的注意力就越少。
安裝
一鍵安裝
將以下內容加入你的 `claude_desktop_config.json` 檔案:
{
"mcpServers": {
"hefestoai": {
"url": "https://hefestoai.narapallc.com/api/mcp-protocol"
}
}
}遠端端點
https://hefestoai.narapallc.com/api/mcp-protocolstreamable-http它能做什麼
工具清單
工具(4)
🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟢pricing
Get HefestoAI pricing information
輸入結構描述
{
"type": "object",
"properties": {},
"required": []
}🟢install
Get installation instructions for HefestoAI
輸入結構描述
{
"type": "object",
"properties": {},
"required": []
}⚪compare(tool)
Compare HefestoAI with other code quality tools
輸入結構描述
{
"type": "object",
"properties": {
"tool": {
"type": "string",
"description": "Tool to compare with (sonarqube, snyk, github-advanced-security, semgrep, claude-code-security)"
}
}
}🟢analyze(code, language)
Analyze a code snippet for quality issues and semantic drift
輸入結構描述
{
"type": "object",
"properties": {
"code": {
"type": "string",
"description": "Code snippet to analyze"
},
"language": {
"type": "string",
"description": "Programming language (python, javascript, etc)"
}
},
"required": [
"code"
]
}社群
證據
近期觀測
已驗證未記錄版本4 個工具
已驗證未記錄版本4 個工具
已驗證未記錄版本4 個工具