titan
GPU compute API: LLM inference (ornith-1.5) on RTX 4080, pay-per-credit in Bitcoin.
我該用這個嗎
品質與安全性
A
根據工具定義與協定合規性的自動化分析。
上下文成本
~336Token(工具定義)
~427 B典型回應大小
極小的注意力影響(128k 上下文的 0.26%)
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": {
"titan": {
"url": "https://titan-mcp.thetempleofdoom.com/mcp"
}
}
}遠端端點
https://titan-mcp.thetempleofdoom.com/mcpstreamable-http它能做什麼
工具清單
工具(5)
🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟢titan_beacon
Check TITAN GPU compute status (free, no key needed).
輸入結構描述
{
"type": "object",
"properties": {},
"title": "titan_beaconArguments"
}⚪titan_generate(prompt, model, api_key)
Run LLM inference on the RTX 4080. Costs 1 credit. Requires an API key.
輸入結構描述
{
"type": "object",
"properties": {
"prompt": {
"title": "Prompt",
"type": "string"
},
"model": {
"default": "qwen3.8fast",
"title": "Model",
"type": "string"
},
"api_key": {
"default": "",
"title": "Api Key",
"type": "string"
}
},
"required": [
"prompt"
],
"title": "titan_generateArguments"
}🟡titan_order(credits)
Create a payment order for TITAN credits (returns a BTCPay checkout URL).
輸入結構描述
{
"type": "object",
"properties": {
"credits": {
"default": 100,
"title": "Credits",
"type": "integer"
}
},
"title": "titan_orderArguments"
}⚪titan_collect_key(order_id)
Collect your TITAN API key after paying (status=settled).
輸入結構描述
{
"type": "object",
"properties": {
"order_id": {
"title": "Order Id",
"type": "string"
}
},
"required": [
"order_id"
],
"title": "titan_collect_keyArguments"
}🟢titan_credits(api_key)
Check remaining credits for an API key.
輸入結構描述
{
"type": "object",
"properties": {
"api_key": {
"default": "",
"title": "Api Key",
"type": "string"
}
},
"title": "titan_creditsArguments"
}社群
證據
近期觀測
已驗證未記錄版本5 個工具