io.github.tenkai2018/ai-business-system-advisor-mcp

pkg:npm:ai-business-system-advisor-mcp

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

transport:: remote + stdio
credential class:: self-provisionable
repo:: https://github.com/tenkai2018/ai-business-system-advisor-mcp

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Tools

analyze_business_context
Summarizes the supplied business context, including customer, offer, workflow, goals, constraints, readiness signals, missing information, and confidence.
shallow
assess_trust_control_risks
Reviews a proposed AI workflow for human review needs, data boundaries, quality controls, escalation triggers, unsafe automation risks, and confidence.
shallow
evaluate_ai_opportunities
Evaluates candidate AI workflow ideas for business value, implementation readiness, repeatability, trust/control risk, warnings, and missing information.
shallow
export_intake_packet
Creates a structured public-safe markdown and JSON intake packet with business context, findings, risks, recommended workflow, missing information, and confidence.
shallow
generate_mini_report
Generates a public-safe mini business system review with snapshot, bottlenecks, opportunities, risks, first workflow, next step, missing information, and confidence.
shallow
identify_bottlenecks
Identifies likely revenue, operations, customer experience, and trust/control bottlenecks from the supplied business context and returns a public-safe summary.
shallow
map_customer_touchpoints
Maps customer-facing workflow stages, trust-sensitive moments, automation-safe areas, human-critical areas, missing information, and confidence.
shallow
recommend_first_workflow
Recommends the safest narrow AI-human workflow to implement first, including roles, review rules, escalation rules, success metrics, and missing information.
shallow
recommend_next_step
Recommends a practical next-step category based on business goal, workflow complexity, implementation readiness, risk level, preferences, and missing information.
shallow

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