# AI Business System Advisor (remote · mcp.prodxsolution.com)

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

- Trust score: 69/100 (medium)
- Change this week: +4
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `mcp.prodxsolution.com`: 69/100 (this document), [markdown](https://verifymcp.io/servers/tenkai2018-ai-business-system-advisor-mcp/ai-business-system-advisor-mcp.md), [page](https://verifymcp.io/servers/tenkai2018-ai-business-system-advisor-mcp/ai-business-system-advisor-mcp)
- npm · `ai-business-system-advisor-mcp`: 31/100, [markdown](https://verifymcp.io/servers/tenkai2018-ai-business-system-advisor-mcp/ai-business-system-advisor-mcp-2.md), [page](https://verifymcp.io/servers/tenkai2018-ai-business-system-advisor-mcp/ai-business-system-advisor-mcp-2)

## Channel facts

- Endpoint: `https://mcp.prodxsolution.com/ai-business-system-advisor/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `0.1.10`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Endpoint Security**: 63/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS not yet verified: we couldn't determine whether a plaintext access path exists.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 73/100
  - 90% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 3212 tokens (~214/item across 15 items; 9 tools + 6 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http tenkai2018-ai-business-system-advisor-mcp https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
```

### Codex

```toml
[mcp_servers.tenkai2018-ai-business-system-advisor-mcp]
url = "https://mcp.prodxsolution.com/ai-business-system-advisor/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "tenkai2018-ai-business-system-advisor-mcp": {
      "type": "remote",
      "url": "https://mcp.prodxsolution.com/ai-business-system-advisor/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add tenkai2018-ai-business-system-advisor-mcp --url https://mcp.prodxsolution.com/ai-business-system-advisor/mcp --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  tenkai2018-ai-business-system-advisor-mcp:
    url: "https://mcp.prodxsolution.com/ai-business-system-advisor/mcp"
```

### Other

```json
{
  "mcpServers": {
    "tenkai2018-ai-business-system-advisor-mcp": {
      "type": "http",
      "url": "https://mcp.prodxsolution.com/ai-business-system-advisor/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-03 (score 69, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-08-01 (score 68, +1)

No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 67, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 67, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-29 (score 66, +1)

No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 65, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 64)

First indexed and scored.

## MCP tools (9)

### `analyze_business_context` (~317 tokens)

Analyze Business Context

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

Input parameters:

- `aiIdea` (string): AI or automation idea the user is considering.
- `businessType` (string): Type of business, such as ecommerce, SaaS, consulting, agency, local service, or solo business.
- `constraints` (array): Known constraints such as budget, team capacity, tools, timeline, compliance needs, or data access.
- `currentGoal` (string): Current business goal the user wants the review to support.
- `currentProblem` (string): Main business or workflow problem the user wants to solve.
- `currentWorkflow` (string): How the relevant workflow currently works, including manual steps, tools, handoffs, and review points.
- `goal90Days` (string): Desired business or workflow outcome over the next 90 days.
- `notes` (string): Any additional context the user wants considered in the review.
- `offer` (string): Core product, service, package, or outcome the business sells.
- `revenueModel` (string): How the business earns revenue, such as projects, retainers, subscriptions, services, or products.
- `riskConcerns` (string): Concerns related to customer trust, brand reputation, legal exposure, sensitive data, or quality control.
- `targetCustomer` (string): Primary customer segment or buyer the business serves.
- `teamSize` (string): Approximate team size and key roles involved in the workflow.

Output parameters:

- `businessSnapshot` (string): Concise public-safe summary of the business and operating context.
- `confidence` (string): Confidence level based on the clarity and completeness of the provided business context.
- `likelyBusinessModel` (string): Likely business model inferred from the supplied context.
- `missingInformation` (array): Information the user should provide to improve diagnostic confidence.
- `primaryConstraintHypothesis` (string): Likely main constraint limiting progress or readiness.
- `readinessSignals` (array): Signals that indicate whether the business is ready for AI-assisted workflow design.
- `targetCustomerSummary` (string): Short summary of the customer segment or buyer context.
- `valuePromiseHypothesis` (string): Hypothesis about the core value promise or outcome the business sells.

### `map_customer_touchpoints` (~287 tokens)

Map Customer Touchpoints

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

Input parameters:

- `aiIdea` (string): AI or automation idea that may affect customer touchpoints.
- `businessType` (string): Type of business being reviewed.
- `currentProblem` (string): Main customer journey or workflow problem the user wants to solve.
- `currentWorkflow` (string): Current workflow steps, tools, owners, and handoffs.
- `customerJourney` (array): Known customer journey stages from first contact through retention.
- `deliveryProcess` (string): How the business delivers the offer or service after onboarding.
- `onboardingProcess` (string): How new customers are welcomed, scoped, educated, or set up.
- `recoveryProcess` (string): How complaints, refunds, exceptions, or service recovery are handled.
- `retentionProcess` (string): How renewals, repeat purchases, referrals, or ongoing customer value are managed.
- `riskConcerns` (string): Concerns about trust, customer experience, brand reputation, privacy, or quality control.
- `salesProcess` (string): How leads are qualified, sold, and converted before delivery begins.
- `supportProcess` (string): How customer questions, issues, tickets, or requests are handled.
- `touchpoints` (array): Specific customer-facing moments, handoffs, or interactions to review.

Output parameters:

- `automationSafeAreas` (array): Areas that appear suitable for AI assistance or automation with low risk.
- `confidence` (string): Confidence level based on the clarity and completeness of the provided business context.
- `humanCriticalAreas` (array): Areas where human review or ownership should remain explicit.
- `missingInformation` (array): Information the user should provide to improve diagnostic confidence.
- `touchpoints` (array): Reviewed customer touchpoints with classification, reason, and suggested control.
- `trustSensitiveMoments` (array): Moments where customer trust, expectations, or brand perception may be at risk.

### `identify_bottlenecks` (~233 tokens)

Identify Bottlenecks

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

Input parameters:

- `aiIdea` (string): Optional AI or automation idea the user is considering.
- `businessContext` (string): Short description of the business model, customers, offer, team, and operating context.
- `businessType` (string): Type of business being reviewed.
- `currentProblem` (string): Main problem or bottleneck the user suspects.
- `currentWorkflow` (string): Current workflow steps, handoffs, tools, and review points.
- `customerComplaints` (string): Known customer complaints, friction points, refunds, or support issues.
- `metrics` (string): Known metrics such as response time, conversion, close rate, cycle time, churn, cost, or error rate.
- `riskConcerns` (string): Concerns about customer trust, brand risk, money, privacy, compliance, or quality control.
- `teamPainPoints` (string): Internal pain points such as repetitive work, slow handoffs, rework, or unclear ownership.

Output parameters:

- `bottleneckSummary` (string): Concise public-safe summary of the most important bottlenecks.
- `confidence` (string): Confidence level based on the clarity and completeness of the provided business context.
- `customerExperienceBottlenecks` (array): Likely issues that create customer friction, unclear expectations, slow responses, or inconsistent service.
- `missingInformation` (array): Information the user should provide to improve diagnostic confidence.
- `mostLikelyRootCause` (string): Most likely underlying cause connecting the visible bottlenecks.
- `operationalBottlenecks` (array): Likely issues that slow delivery, increase manual work, create rework, or reduce efficiency.
- `revenueBottlenecks` (array): Likely issues that reduce sales, conversion, qualified calls, deal speed, or revenue growth.
- `trustControlBottlenecks` (array): Likely gaps in review rules, approvals, escalation triggers, data boundaries, or quality control.

### `evaluate_ai_opportunities` (~160 tokens)

Evaluate AI Opportunities

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

Input parameters:

- `aiIdea` (string): Specific AI or automation idea the user wants evaluated.
- `businessContext` (string): Short description of the business, customers, offer, and current operating context.
- `businessType` (string): Type of business being reviewed.
- `candidateUseCases` (array): Candidate AI workflow ideas to evaluate.
- `currentProblem` (string): Main problem the AI opportunities should help solve.
- `currentWorkflow` (string): Current workflow before AI or automation.
- `riskConcerns` (string): Concerns about customer trust, brand risk, money, privacy, compliance, or quality control.

Output parameters:

- `confidence` (string): Confidence level based on the clarity and completeness of the provided business context.
- `missingInformation` (array): Information the user should provide to improve diagnostic confidence.
- `opportunities` (array): Evaluated AI opportunities with value, readiness, risk, and control guidance.
- `recommendedFirstOpportunity` (string): Best first opportunity to consider based on value, readiness, and risk.
- `warnings` (array): Warnings about high-risk, premature, or unsafe automation patterns.

### `assess_trust_control_risks` (~309 tokens)

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.

Input parameters:

- `aiIdea` (string): Specific AI or automation idea the user is considering.
- `businessType` (string): Type of business being reviewed.
- `canAffectBrandTrust` (boolean): Whether the workflow can affect brand reputation, customer expectations, or public trust.
- `canAffectMoney` (boolean): Whether the workflow can influence pricing, refunds, payments, scope, or financial decisions.
- `currentControls` (string): Existing review, approval, QA, escalation, or monitoring controls.
- `currentProblem` (string): Main business or workflow problem the user wants to solve.
- `currentWorkflow` (string): Current workflow before AI or automation.
- `customerFacing` (boolean): Whether the workflow directly affects customers or customer-facing messages.
- `proposedWorkflow` (string): Proposed workflow design, including what AI would do and what humans would review.
- `requiresExpertJudgment` (boolean): Whether the workflow needs professional, strategic, legal, financial, HR, or domain judgment.
- `riskConcerns` (string): Known concerns about customer trust, brand risk, compliance, money, privacy, or quality control.
- `usesSensitiveData` (boolean): Whether the workflow may use private, regulated, or sensitive business/customer data.
- `workflowIdea` (string): AI workflow or agent idea to assess for trust and control risk.

Output parameters:

- `confidence` (string): Confidence level based on the clarity and completeness of the provided business context.
- `dataBoundaryWarnings` (array): Warnings about sensitive data, privacy, access boundaries, or inappropriate inputs.
- `escalationTriggers` (array): Conditions that should escalate to a human owner or expert reviewer.
- `humanReviewRules` (array): Rules for when a human must review, approve, or override AI output.
- `missingInformation` (array): Information the user should provide to improve risk assessment confidence.
- `notRecommendedActions` (array): Actions that should not be automated in the current version.
- `requiredControls` (array): Controls needed before the workflow should be piloted or expanded.
- `riskLevel` (string): Estimated risk level for the workflow or recommendation.
- `riskSummary` (string): Concise public-safe summary of the main trust and control risks.

### `recommend_first_workflow` (~371 tokens)

Recommend First Workflow

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

Input parameters:

- `aiIdea` (string): AI or automation idea the user is considering.
- `bottlenecks` (array): Known or suspected bottlenecks the first workflow should address.
- `businessType` (string): Type of business, such as ecommerce, SaaS, consulting, agency, local service, or solo business.
- `constraints` (array): Known constraints such as budget, team capacity, tools, timeline, compliance needs, or data access.
- `currentGoal` (string): Current business goal the user wants the review to support.
- `currentProblem` (string): Main business or workflow problem the user wants to solve.
- `currentWorkflow` (string): How the relevant workflow currently works, including manual steps, tools, handoffs, and review points.
- `goal90Days` (string): Desired business or workflow outcome over the next 90 days.
- `notes` (string): Any additional context the user wants considered in the review.
- `offer` (string): Core product, service, package, or outcome the business sells.
- `opportunities` (array): AI opportunities already identified or under consideration.
- `revenueModel` (string): How the business earns revenue, such as projects, retainers, subscriptions, services, or products.
- `riskConcerns` (string): Concerns related to customer trust, brand reputation, legal exposure, sensitive data, or quality control.
- `risks` (array): Known risks or control concerns that should shape the workflow design.
- `targetCustomer` (string): Primary customer segment or buyer the business serves.
- `teamSize` (string): Approximate team size and key roles involved in the workflow.

Output parameters:

- `aiRole` (string): What AI should observe, summarize, draft, classify, or prepare.
- `confidence` (string): Confidence level based on the clarity and completeness of the provided business context.
- `escalationRule` (string): Rule for cases that should escalate to a human owner or expert.
- `expectedOutcome` (string): Expected business outcome if the workflow is piloted successfully.
- `firstImplementationScope` (string): Smallest practical pilot scope for the first version.
- `humanRole` (string): What a human should approve, decide, handle, or monitor.
- `missingInformation` (array): Information the user should provide to improve workflow recommendation confidence.
- `recommendedWorkflow` (string): Narrow AI-human workflow recommended as the safest first implementation.
- `reviewRule` (string): Rule for when human review is required before output or action.
- `successMetrics` (array): Practical metrics to evaluate workflow pilot success.
- `whyThisWorkflow` (string): Reason this workflow is a practical first candidate based on value, readiness, and risk.
- `workflowCategory` (string): Category of workflow, such as sales prep, support triage, QA, reporting, or operations.

### `generate_mini_report` (~466 tokens)

Generate Mini Report

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

Input parameters:

- `aiIdea` (string): AI or automation idea the user is considering.
- `bottlenecks` (array): Known bottlenecks to include in the mini review.
- `businessSnapshot` (string): Existing business snapshot to include or refine in the mini review.
- `businessType` (string): Type of business, such as ecommerce, SaaS, consulting, agency, local service, or solo business.
- `confidence` (string): Optional confidence level to carry into the report.
- `constraints` (array): Known constraints such as budget, team capacity, tools, timeline, compliance needs, or data access.
- `currentGoal` (string): Current business goal the user wants the review to support.
- `currentProblem` (string): Main business or workflow problem the user wants to solve.
- `currentWorkflow` (string): How the relevant workflow currently works, including manual steps, tools, handoffs, and review points.
- `goal90Days` (string): Desired business or workflow outcome over the next 90 days.
- `nextStep` (string): Existing next-step recommendation to include or refine.
- `notes` (string): Any additional context the user wants considered in the review.
- `offer` (string): Core product, service, package, or outcome the business sells.
- `opportunities` (array): Known AI opportunities to include in the mini review.
- `preferredNextStep` (string): User preference for self-guided, diagnostic, documentation, build, or review support.
- `recommendedWorkflow` (string): Existing first workflow recommendation to include or refine.
- `revenueModel` (string): How the business earns revenue, such as projects, retainers, subscriptions, services, or products.
- `riskConcerns` (string): Concerns related to customer trust, brand reputation, legal exposure, sensitive data, or quality control.
- `risks` (array): Known trust, control, customer, or implementation risks to include.
- `targetCustomer` (string): Primary customer segment or buyer the business serves.
- `teamSize` (string): Approximate team size and key roles involved in the workflow.

Output parameters:

- `confidence` (string): Confidence level based on the clarity and completeness of the provided business context.
- `disclaimer` (string): Public safety note explaining the limits of the review.
- `missingInformation` (array): Information the user should provide to improve report confidence.
- `recommendedAction` (string): Most practical next action based on the supplied context.
- `reportMarkdown` (string): Public-safe mini review formatted as markdown.
- `shortSummary` (string): Brief summary of the review result.

### `recommend_next_step` (~489 tokens)

Recommend Next Step

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

Input parameters:

- `aiIdea` (string): AI or automation idea the user is considering.
- `businessType` (string): Type of business, such as ecommerce, SaaS, consulting, agency, local service, or solo business.
- `constraints` (array): Known constraints such as budget, team capacity, tools, timeline, compliance needs, or data access.
- `currentGoal` (string): Current business goal the user wants the review to support.
- `currentProblem` (string): Main business or workflow problem the user wants to solve.
- `currentWorkflow` (string): How the relevant workflow currently works, including manual steps, tools, handoffs, and review points.
- `goal90Days` (string): Desired business or workflow outcome over the next 90 days.
- `hasExistingAutomation` (boolean): Whether the business already has automation or AI workflows in place.
- `implementationReadiness` (string): How ready the business appears for implementation.
- `notes` (string): Any additional context the user wants considered in the review.
- `offer` (string): Core product, service, package, or outcome the business sells.
- `preference` (string): User's preferred support style.
- `problemComplexity` (string): Estimated complexity of the business or workflow problem.
- `readiness` (string): Simplified readiness level if already known.
- `revenueModel` (string): How the business earns revenue, such as projects, retainers, subscriptions, services, or products.
- `riskConcerns` (string): Concerns related to customer trust, brand reputation, legal exposure, sensitive data, or quality control.
- `riskLevel` (string): Estimated risk level or uncertainty for the workflow.
- `targetCustomer` (string): Primary customer segment or buyer the business serves.
- `teamSize` (string): Approximate team size and key roles involved in the workflow.
- `timeline` (string): Desired timeline for review, documentation, pilot, or implementation.
- `userGoal` (string): Goal the user wants the next step to support.
- `wantsDoneForYou` (boolean): Whether the user prefers implementation support rather than self-guided work.
- `wantsSelfGuided` (boolean): Whether the user prefers self-guided resources or templates.

Output parameters:

- `alternativePaths` (array): Other reasonable next-step categories the user could consider.
- `confidence` (string): Confidence level based on the clarity and completeness of the provided business context.
- `missingInformation` (array): Information the user should provide to improve routing confidence.
- `readinessLevel` (string): Estimated readiness level for the recommended path.
- `reason` (string): Reason this next-step category fits the supplied context.
- `recommendedPath` (string): Recommended next-step category.
- `suggestedAction` (string): Practical action the user can take next.

### `export_intake_packet` (~483 tokens)

Export Intake Packet

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

Input parameters:

- `aiIdea` (string): AI or automation idea the user is considering.
- `bottleneckSummary` (object): Structured bottleneck findings from a prior tool result.
- `businessContext` (object): Structured business context from a prior tool result or user notes.
- `businessType` (string): Type of business, such as ecommerce, SaaS, consulting, agency, local service, or solo business.
- `constraints` (array): Known constraints such as budget, team capacity, tools, timeline, compliance needs, or data access.
- `currentGoal` (string): Current business goal the user wants the review to support.
- `currentProblem` (string): Main business or workflow problem the user wants to solve.
- `currentWorkflow` (string): How the relevant workflow currently works, including manual steps, tools, handoffs, and review points.
- `goal90Days` (string): Desired business or workflow outcome over the next 90 days.
- `notes` (string): Any additional context the user wants considered in the review.
- `offer` (string): Core product, service, package, or outcome the business sells.
- `opportunitySummary` (object): Structured AI opportunity findings from a prior tool result.
- `preferredNextStep` (string): Preferred next-step category or support style to include in the packet.
- `recommendedNextStep` (object): Structured next-step recommendation from a prior tool result.
- `recommendedWorkflow` (object): Structured first workflow recommendation from a prior tool result.
- `revenueModel` (string): How the business earns revenue, such as projects, retainers, subscriptions, services, or products.
- `riskConcerns` (string): Concerns related to customer trust, brand reputation, legal exposure, sensitive data, or quality control.
- `riskSummary` (object): Structured trust and control risk findings from a prior tool result.
- `targetCustomer` (string): Primary customer segment or buyer the business serves.
- `teamSize` (string): Approximate team size and key roles involved in the workflow.
- `touchpointMap` (object): Structured customer touchpoint map from a prior tool result.
- `userNotes` (string): Additional notes the user wants included in the intake packet.

Output parameters:

- `confidence` (string): Confidence level based on the clarity and completeness of the provided business context.
- `missingInformation` (array): Information the user should provide before deeper review or implementation.
- `packetJson` (object): Structured intake packet data for handoff or deeper review.
- `packetMarkdown` (string): Public-safe intake packet formatted as markdown.
- `recommendedPrivateReview` (string): Public-safe recommendation for the next deeper review category.

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/tenkai2018-ai-business-system-advisor-mcp/ai-business-system-advisor-mcp#diagnostics

## Score history

- 2026-08-03: 69
- 2026-08-02: 68
- 2026-08-01: 68
- 2026-07-31: 67
- 2026-07-30: 67
- 2026-07-29: 66
- 2026-07-28: 65
- 2026-07-27: 65
- 2026-07-26: 64

## Links

- Remote endpoint: https://mcp.prodxsolution.com/ai-business-system-advisor/mcp
- Repository: https://github.com/tenkai2018/ai-business-system-advisor-mcp
- Changelog RSS feed: https://verifymcp.io/servers/tenkai2018-ai-business-system-advisor-mcp/ai-business-system-advisor-mcp/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/tenkai2018-ai-business-system-advisor-mcp/ai-business-system-advisor-mcp/changelog.json
- HTML version of this page: https://verifymcp.io/servers/tenkai2018-ai-business-system-advisor-mcp/ai-business-system-advisor-mcp