Vendor Regulatory Evidence
Resolve a vendor and buy normalized public OSHA, EPA, and SAM exclusion evidence with provenance.
我該用這個嗎
品質與安全性
A
發現項目(1)
- LOW在 build_vendor_evidence_package 中
根據工具定義與協定合規性的自動化分析。
上下文成本
~333Token(工具定義)
~743 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": {
"agent-services-001": {
"url": "https://experiment-001-production-90c3.up.railway.app/mcp"
}
}
}遠端端點
https://experiment-001-production-90c3.up.railway.app/mcpstreamable-http它能做什麼
工具清單
工具(3)
🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟢resolve_vendor(aliases, city, company_name, epa_frs_id, state, ...)
Resolve a U.S. vendor before payment; ambiguity never creates a charge.
輸入結構描述
{
"type": "object",
"properties": {
"aliases": {
"items": {
"maxLength": 160,
"type": "string"
},
"maxItems": 10,
"type": "array"
},
"city": {
"maxLength": 100,
"type": "string"
},
"company_name": {
"maxLength": 160,
"type": "string"
},
"epa_frs_id": {
"maxLength": 20,
"type": "string"
},
"state": {
"pattern": "^[A-Z]{2}$",
"type": "string"
},
"street_address": {
"maxLength": 200,
"type": "string"
},
"uei": {
"maxLength": 12,
"type": "string"
},
"zip_code": {
"maxLength": 10,
"type": "string"
}
},
"required": [
"company_name",
"state"
],
"additionalProperties": false
}🟢get_vendor_regulatory_records(vendor_token)
Purchase normalized OSHA, EPA ECHO, and public SAM exclusion records for a resolved vendor.
輸入結構描述
{
"type": "object",
"properties": {
"vendor_token": {
"type": "string"
}
},
"required": [
"vendor_token"
],
"additionalProperties": false
}🟢build_vendor_evidence_package(vendor_token)
Purchase a classified, source-backed vendor regulatory evidence package.
輸入結構描述
{
"type": "object",
"properties": {
"vendor_token": {
"type": "string"
}
},
"required": [
"vendor_token"
],
"additionalProperties": false
}社群
證據
近期觀測
已驗證未記錄版本3 個工具
已驗證未記錄版本3 個工具
已驗證未記錄版本3 個工具