AI Business System Advisor

io.github.tenkai2018由 GitHub 帳號 tenkai2018 發布v0.1.10更新於 Oct 24, 2026

Find the safest first AI workflow before investing in AI agents or automation.

已驗證Streamable HTTP可網頁執行效率與工作流商業與電商

概覽

AI 產生的概覽

一個業務顧問類 MCP 伺服器,用來檢視企業流程與 AI 構想,並推薦第一個安全的 AI 與人工協作流程。

可以做什麼
分析業務背景、客戶、產品、流程與目標,並梳理客戶接觸點與信任敏感環節。找出營收、營運與客戶體驗方面的瓶頸。評估候選 AI 流程構想在價值、落地準備度與信任控制風險上的表現,並檢視人工複核、資料界線與升級機制需求。推薦一個範圍較窄的第一個 AI 與人工協作流程,包含角色、複核與升級規則及成功指標。產生對外安全的迷你檢視報告,給出下一步類別建議,並匯出結構化的 markdown 與 JSON 資訊收集包。
適用情境
適合創辦人、營運者、顧問或小團隊在決定先自動化哪個流程時使用,或在投入自動化之前評估某個 AI 代理構想對客戶接觸環節是否安全。
執行需求
可作為遠端 streamable HTTP 端點使用,也可透過 npx 以本機 npm 套件形式執行,需要 Node.js。未宣告驗證、API 金鑰或環境變數。使用遠端端點需要網路存取。
安裝前請注意
提交的業務背景會傳送到伺服器;README 說明不要傳送密碼、API 金鑰、原始私人客戶紀錄、受監管資料或機密合約。輸出僅為初步檢視,不構成法律、財務、醫療、人力資源或法遵建議。伺服器會拒絕提供私有實作細節的請求。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 AI Business System Advisor,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.tenkai2018%2Fai-business-system-advisor-mcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "ai-business-system-advisor": {
      "type": "http",
      "url": "https://mcp.prodxsolution.com/ai-business-system-advisor/mcp"
    }
  }
}

README

AI Business System Advisor MCP

[smithery badge]

Find the safest first AI workflow for your business.

AI Business System Advisor MCP helps founders, operators, consultants, and small teams review business workflows, AI opportunities, trust/control risks, and implementation readiness before building AI agents or automation.

It produces a public-safe mini review, recommends a practical first AI-human workflow, and exports a structured intake packet for deeper review or implementation planning.

This MCP is designed for business-system thinking, not generic chatbot recommendations or tool-first automation.

What It Does

  • Reviews business context, target customers, offers, workflows, and goals.
  • Identifies operational bottlenecks and customer journey friction.
  • Evaluates AI workflow ideas for value, readiness, and trust/control risk.
  • Recommends a narrow first AI-human workflow with review and escalation rules.
  • Generates mini reports and structured intake packets.

Who It Is For

  • Solo founders
  • Service businesses
  • B2B consultants
  • Agency owners
  • Operators
  • Small teams exploring AI agents or automation

Problems It Helps Solve

  • Which workflow should I automate first?
  • Is this AI agent idea safe for my customer experience?
  • Where should humans stay in control?
  • What trust/control risks exist in this workflow?
  • What information is missing before implementation?
  • How should I prepare this business for AI automation?

Use With MCP Clients

For Claude Desktop, Cursor, Windsurf, Codex, or another stdio MCP client:

json
{  "mcpServers": {    "ai-business-system-advisor": {      "command": "npx",      "args": ["-y", "ai-business-system-advisor-mcp"]    }  }}

You can also run the package directly:

bash
npx -y ai-business-system-advisor-mcp

For remote MCP clients, use:

text
https://mcp.prodxsolution.com/ai-business-system-advisor/mcp

Smithery listing:

text
https://smithery.ai/servers/prodxsolution/ai-business-system-advisor-mcp

Available Tools

  • analyze_business_context
  • map_customer_touchpoints
  • identify_bottlenecks
  • evaluate_ai_opportunities
  • assess_trust_control_risks
  • recommend_first_workflow
  • generate_mini_report
  • recommend_next_step
  • export_intake_packet

Available Prompts

  • run_mini_business_system_review
  • evaluate_ai_workflow_idea
  • prepare_diagnostic_intake
  • governance_gap_snapshot

Available Resources

  • Overview
  • How it works
  • Readiness guide
  • Sample mini report
  • Sample intake packet
  • Privacy note

Example Questions

Ask your AI assistant:

  • Review my business and identify the safest first AI workflow to improve.
  • Is this AI agent idea safe for customer support, refunds, and complaints?
  • Where should humans stay in control in this workflow?
  • What trust/control risks should I consider before automating this process?
  • Generate a mini business system review and tell me what information is missing.
  • Export an intake packet for deeper workflow review.

Example Output

text
Mini Business System Review
Business Snapshot:A service agency sells conversion and landing page work to ecommerce brands. Sales capacity is constrained by manual lead research, inconsistent qualification, and proposal drafting.
Likely Bottlenecks:- Lead research takes too long before a sales call.- Proposal quality depends on expert availability.- Customer-facing claims need clearer approval rules.
Recommended First Workflow:AI prepares a lead research and qualification brief, then drafts proposal sections from approved language. A human reviews lead fit, scope, pricing, claims, and final customer-facing messages.
Trust And Control Risk:Medium. The workflow can affect revenue, brand trust, and customer expectations, so AI should prepare work but not send promises or pricing without approval.
Success Metrics:- qualified calls booked- proposal cycle time- human edit rate- lead-to-call conversion
Missing Information:ideal customer criteria, approved claims, disallowed claims, proposal rules, escalation triggers, and success metrics

Privacy And Security

The server is read-mostly and does not intentionally persist submitted business context. Do not send passwords, API keys, raw private customer records, regulated data, or confidential contracts.

Outputs are first-pass reviews based on the information provided. They are not legal, financial, medical, HR, or compliance advice.

Public Safety Boundary

The server uses business-facing language and refuses requests for private implementation details. Public outputs focus on business context, workflow fit, risk controls, recommended next steps, and missing information.

It does not expose protected implementation details, exact formulas, confidential designs, or client-specific confidential data.

Roadmap

  • More fictional sample reviews for common business types.
  • Guided public workflow for mini reviews and intake packets.
  • Additional public resources for AI workflow readiness and human review design.

來源:README.md,提交 2053985

工具

9

analyze_business_context

Analyze Business Context

Summarizes the supplied business context, including customer, offer, workflow, goals, constraints, readiness signals, missing information, and confidence.

輸入參數notesofferaiIdeateamSizegoal90DaysconstraintscurrentGoalbusinessTyperevenueModelriskConcernscurrentProblemtargetCustomer另有 1 個

map_customer_touchpoints

Map Customer Touchpoints

Maps customer-facing workflow stages, trust-sensitive moments, automation-safe areas, human-critical areas, missing information, and confidence.

輸入參數aiIdeatouchpointsbusinessTyperiskConcernssalesProcesscurrentProblemsupportProcesscurrentWorkflowcustomerJourneydeliveryProcessrecoveryProcessretentionProcess另有 1 個

identify_bottlenecks

Identify Bottlenecks

Identifies likely revenue, operations, customer experience, and trust/control bottlenecks from the supplied business context and returns a public-safe summary.

輸入參數aiIdeametricsbusinessTyperiskConcernscurrentProblemteamPainPointsbusinessContextcurrentWorkflowcustomerComplaints

evaluate_ai_opportunities

Evaluate AI Opportunities

Evaluates candidate AI workflow ideas for business value, implementation readiness, repeatability, trust/control risk, warnings, and missing information.

輸入參數aiIdeabusinessTyperiskConcernscurrentProblembusinessContextcurrentWorkflowcandidateUseCases

assess_trust_control_risks

Assess Trust And Control Risks

Reviews a proposed AI workflow for human review needs, data boundaries, quality controls, escalation triggers, unsafe automation risks, and confidence.

輸入參數aiIdeabusinessTyperiskConcernsworkflowIdeacanAffectMoneycurrentProblemcustomerFacingcurrentControlscurrentWorkflowproposedWorkflowusesSensitiveDatacanAffectBrandTrust另有 1 個

recommend_first_workflow

Recommend First Workflow

Recommends the safest narrow AI-human workflow to implement first, including roles, review rules, escalation rules, success metrics, and missing information.

輸入參數notesofferrisksaiIdeateamSizegoal90DaysbottlenecksconstraintscurrentGoalbusinessTyperevenueModelriskConcerns另有 4 個

generate_mini_report

Generate Mini Report

Generates a public-safe mini business system review with snapshot, bottlenecks, opportunities, risks, first workflow, next step, missing information, and confidence.

輸入參數notesofferrisksaiIdeanextStepteamSizeconfidencegoal90DaysbottlenecksconstraintscurrentGoalbusinessType另有 9 個

recommend_next_step

Recommend Next Step

Recommends a practical next-step category based on business goal, workflow complexity, implementation readiness, risk level, preferences, and missing information.

輸入參數notesofferaiIdeateamSizetimelineuserGoalreadinessriskLevelgoal90DayspreferenceconstraintscurrentGoal另有 11 個

export_intake_packet

Export Intake Packet

Creates a structured public-safe markdown and JSON intake packet with business context, findings, risks, recommended workflow, missing information, and confidence.

輸入參數notesofferaiIdeateamSizeuserNotesgoal90DaysconstraintscurrentGoalriskSummarybusinessTyperevenueModelriskConcerns另有 10 個

版本歷史

1
  1. v0.1.10最新Sep 16, 2026

評分

已滿足適用檢查項的 90%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分

    請在儲存庫或註冊中心條目中宣告授權條款。