AI Business System Advisor

io.github.tenkai2018Published by GitHub account tenkai2018v0.1.10Updated Oct 24, 2026

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

VerifiedStreamable HTTPWeb executableProductivity & WorkflowBusiness & Commerce

Overview

AI-generated overview

A business advisory MCP server that reviews a business's workflows and AI ideas and recommends a safe first AI-human workflow.

What you can do
Review business context, customers, offers, workflows and goals, and map customer touchpoints and trust-sensitive moments. Identify revenue, operations and customer-experience bottlenecks. Evaluate candidate AI workflow ideas for value, readiness and trust/control risk, and assess human review, data boundaries and escalation needs. Recommend a narrow first AI-human workflow with roles, review and escalation rules, and success metrics. Generate a public-safe mini review, suggest a next-step category, and export a structured markdown and JSON intake packet.
When to use it
Use it when a founder, operator, consultant or small team wants to decide which workflow to automate first, or check whether an AI agent idea is safe for customer-facing work before investing in automation.
Requirements
Runs as a remote streamable HTTP endpoint or as a local npm package via npx with Node.js. No authentication, API keys or environment variables are declared. Network access is needed for the remote endpoint.
Before you install
Submitted business context is sent to the server; the README says not to send passwords, API keys, raw private customer records, regulated data or confidential contracts. Outputs are first-pass reviews, not legal, financial, medical, HR or compliance advice. The server refuses requests for private implementation details.

Installation

In SourceWeft

  1. Open AI Business System Advisor in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.tenkai2018%2Fai-business-system-advisor-mcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "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.

Source: README.md at commit 2053985

Tools

9

analyze_business_context

Analyze Business Context

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

ParametersnotesofferaiIdeateamSizegoal90DaysconstraintscurrentGoalbusinessTyperevenueModelriskConcernscurrentProblemtargetCustomer+1 more

map_customer_touchpoints

Map Customer Touchpoints

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

ParametersaiIdeatouchpointsbusinessTyperiskConcernssalesProcesscurrentProblemsupportProcesscurrentWorkflowcustomerJourneydeliveryProcessrecoveryProcessretentionProcess+1 more

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.

ParametersaiIdeametricsbusinessTyperiskConcernscurrentProblemteamPainPointsbusinessContextcurrentWorkflowcustomerComplaints

evaluate_ai_opportunities

Evaluate AI Opportunities

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

ParametersaiIdeabusinessTyperiskConcernscurrentProblembusinessContextcurrentWorkflowcandidateUseCases

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.

ParametersaiIdeabusinessTyperiskConcernsworkflowIdeacanAffectMoneycurrentProblemcustomerFacingcurrentControlscurrentWorkflowproposedWorkflowusesSensitiveDatacanAffectBrandTrust+1 more

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.

ParametersnotesofferrisksaiIdeateamSizegoal90DaysbottlenecksconstraintscurrentGoalbusinessTyperevenueModelriskConcerns+4 more

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.

ParametersnotesofferrisksaiIdeanextStepteamSizeconfidencegoal90DaysbottlenecksconstraintscurrentGoalbusinessType+9 more

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.

ParametersnotesofferaiIdeateamSizetimelineuserGoalreadinessriskLevelgoal90DayspreferenceconstraintscurrentGoal+11 more

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.

ParametersnotesofferaiIdeateamSizeuserNotesgoal90DaysconstraintscurrentGoalriskSummarybusinessTyperevenueModelriskConcerns+10 more

Version history

1
  1. v0.1.10LatestSep 16, 2026

Score

90% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.