mcp server
AI Business System Advisor
Find the safest first AI workflow before investing in AI agents or automation.
Description as published by the maintainer. Source
- version 0.1.10
- active
- workflow automation
active — Registry entry last updated 2026-05-31. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
What this server can do
9 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
analyze_business_context(notes, offer, aiIdea, teamSize, goal90Days, constraints, currentGoal, businessType, revenueModel, riskConcerns, currentProblem, targetCustomer, currentWorkflow)- Summarizes the supplied business context, including customer, offer, workflow, goals, constraints, readiness signals, missing information, and confidence.
assess_trust_control_risks(aiIdea, businessType, riskConcerns, workflowIdea, canAffectMoney, currentProblem, customerFacing, currentControls, currentWorkflow, proposedWorkflow, usesSensitiveData, canAffectBrandTrust, requiresExpertJudgment)- Reviews a proposed AI workflow for human review needs, data boundaries, quality controls, escalation triggers, unsafe automation risks, and confidence.
evaluate_ai_opportunities(aiIdea, businessType, riskConcerns, currentProblem, businessContext, currentWorkflow, candidateUseCases)- Evaluates candidate AI workflow ideas for business value, implementation readiness, repeatability, trust/control risk, warnings, and missing information.
export_intake_packet(notes, offer, aiIdea, teamSize, userNotes, goal90Days, constraints, currentGoal, riskSummary, businessType, revenueModel, riskConcerns, touchpointMap, currentProblem, targetCustomer, businessContext, currentWorkflow, bottleneckSummary, preferredNextStep, opportunitySummary, recommendedNextStep, recommendedWorkflow)- Creates a structured public-safe markdown and JSON intake packet with business context, findings, risks, recommended workflow, missing information, and confidence.
generate_mini_report(notes, offer, risks, aiIdea, nextStep, teamSize, confidence, goal90Days, bottlenecks, constraints, currentGoal, businessType, revenueModel, riskConcerns, opportunities, currentProblem, targetCustomer, currentWorkflow, businessSnapshot, preferredNextStep, recommendedWorkflow)- Generates a public-safe mini business system review with snapshot, bottlenecks, opportunities, risks, first workflow, next step, missing information, and confidence.
identify_bottlenecks(aiIdea, metrics, businessType, riskConcerns, currentProblem, teamPainPoints, businessContext, currentWorkflow, customerComplaints)- Identifies likely revenue, operations, customer experience, and trust/control bottlenecks from the supplied business context and returns a public-safe summary.
map_customer_touchpoints(aiIdea, touchpoints, businessType, riskConcerns, salesProcess, currentProblem, supportProcess, currentWorkflow, customerJourney, deliveryProcess, recoveryProcess, retentionProcess, onboardingProcess)- Maps customer-facing workflow stages, trust-sensitive moments, automation-safe areas, human-critical areas, missing information, and confidence.
recommend_first_workflow(notes, offer, risks, aiIdea, teamSize, goal90Days, bottlenecks, constraints, currentGoal, businessType, revenueModel, riskConcerns, opportunities, currentProblem, targetCustomer, currentWorkflow)- Recommends the safest narrow AI-human workflow to implement first, including roles, review rules, escalation rules, success metrics, and missing information.
recommend_next_step(notes, offer, aiIdea, teamSize, timeline, userGoal, readiness, riskLevel, goal90Days, preference, constraints, currentGoal, businessType, revenueModel, riskConcerns, currentProblem, targetCustomer, currentWorkflow, wantsDoneForYou, wantsSelfGuided, problemComplexity, hasExistingAutomation, implementationReadiness)- Recommends a practical next-step category based on business goal, workflow complexity, implementation readiness, risk level, preferences, and missing information.
Last successful function declaration observed on . Source: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| Latest published version | 0.1.10 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-05-31 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| First listed in the MCP Registry | 2026-05-31 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| mcp tools declared | 9 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | mcp.prodxsolution.com | |
| mcp endpoint status | ok | The server listed 9 functions when asked. | as of probe | mcp.prodxsolution.com |
Where to get it
This record as data
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