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

up checked 2026-11-11T08:38:08.145Z

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Publisher-provided title

AI Business System Advisor

Publisher-provided description

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

Summary by lookupd

Analyzes business context and recommends a safe first AI workflow with risk review, bottleneck identification, and intake reports.

Install

Claude Code, remote (streamable-http)

claude mcp add --transport http ai-business-system-advisor https://mcp.prodxsolution.com/ai-business-system-advisor/mcp

Claude Code, npm package (stdio)

claude mcp add ai-business-system-advisor -- npx -y ai-business-system-advisor-mcp

Codex, remote (streamable-http)

codex mcp add ai-business-system-advisor --url https://mcp.prodxsolution.com/ai-business-system-advisor/mcp

Codex, npm package (stdio)

codex mcp add ai-business-system-advisor -- npx -y ai-business-system-advisor-mcp

Cursor, remote (streamable-http) → .cursor/mcp.json

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

Cursor, npm package (stdio) → .cursor/mcp.json

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

Other clients: docs. Or tell your agent: Set up lookupd for me: read https://lookupd.com/agent.md and follow it.

Tools (9 tools)

Publisher-provided text

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

Details

• Version: 0.1.10
• Transports: streamable-http, stdio
• Uptime (7 days): 100%
• Median latency: 461 ms
• First indexed: 2026-11-01T09:56:53.990Z
• Last seen in registry: 2026-11-01T09:56:54.025Z
• Repository: https://github.com/tenkai2018/ai-business-system-advisor-mcp

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• Last crawl: 2026-11-11T16:17:25.167Z
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