# AI Recommendation Readiness Audit | The Black Friday Agency (remote · canairecommendmybusiness.com)

Can AI confidently recommend your business? The AI Recommendation Readiness Audit shows whether your

- Trust score: 70/100 (medium)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-20

## Components

- remote · `canairecommendmybusiness.com`: 70/100 (this document), [markdown](https://verifymcp.io/servers/janoliverautomation-stack-canairecommendmybusiness-com/api-mcp.md), [page](https://verifymcp.io/servers/janoliverautomation-stack-canairecommendmybusiness-com/api-mcp)

## Channel facts

- Endpoint: `https://canairecommendmybusiness.com/api/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.0`

## 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 2026-09-20.

- **Endpoint Security**: 57/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation not fully verified: no authorisation is required to call this server, and 2 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe.
  - HTTPS is enforced; there's no plaintext access path.
  - 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
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 330 tokens (~165/item across 2 items; 2 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 53/100
  - Stability observed for 16 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.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 2 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 3 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 60/100
  - Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28.

## Install

### How do I install the AI Recommendation Readiness Audit | The Black Friday Agency MCP server?

AI Recommendation Readiness Audit | The Black Friday Agency is a hosted endpoint at https://canairecommendmybusiness.com/api/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http janoliverautomation-stack-canairecommendmybusine 'https://canairecommendmybusiness.com/api/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "janoliverautomation-stack-canairecommendmybusine": {
      "url": "https://canairecommendmybusiness.com/api/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "janoliverautomation-stack-canairecommendmybusine": {
      "type": "http",
      "url": "https://canairecommendmybusiness.com/api/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.janoliverautomation-stack-canairecommendmybusine]
url = "https://canairecommendmybusiness.com/api/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "janoliverautomation-stack-canairecommendmybusine": {
      "type": "remote",
      "url": "https://canairecommendmybusiness.com/api/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add janoliverautomation-stack-canairecommendmybusine --url 'https://canairecommendmybusiness.com/api/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  janoliverautomation-stack-canairecommendmybusine:
    url: "https://canairecommendmybusiness.com/api/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "janoliverautomation-stack-canairecommendmybusine": {
      "Transport": "http",
      "Url": "https://canairecommendmybusiness.com/api/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add janoliverautomation-stack-canairecommendmybusine -t streamable-http -u 'https://canairecommendmybusiness.com/api/mcp'
```

### Other

```json
{
  "mcpServers": {
    "janoliverautomation-stack-canairecommendmybusine": {
      "type": "http",
      "url": "https://canairecommendmybusiness.com/api/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.

### 2026-09-20 (score 70, +1)

No change was recorded against any check on this day. Stability & Change Management went from 50 to 53. That category is still filling its 30-day observation window: 15 days of observed history at the previous scan, 16 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-18 (score 69, +1)

No change was recorded against any check on this day. Stability & Change Management went from 43 to 47. That category is still filling its 30-day observation window: 13 days of observed history at the previous scan, 14 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-15 (score 68, +1)

No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-13 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 27 to 30. That category is still filling its 30-day observation window: 8 days of observed history at the previous scan, 9 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-11 (score 66, +1)

No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-09 (score 65, +1)

No change was recorded against any check on this day. Stability & Change Management went from 13 to 17. That category is still filling its 30-day observation window: 4 days of observed history at the previous scan, 5 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-07 (score 64, +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.

### 2026-09-05 (score 63, +1)

- [functional improvement] Schema quality: 238 → 165
- [functional improvement] Stability: unverified → 0.03
- [functional improvement] Tool “assess_ai_recommendation_readiness” now declares an output schema
- [functional] First check of Tool coverage: 100
- [functional] New tool “get_ai_readiness_framework”
- [cosmetic] “assess_ai_recommendation_readiness” reworded the description of “goals”

## MCP tools (2)

### `assess_ai_recommendation_readiness` (~201 tokens)

Assess AI Recommendation Readiness

Assesses whether a business is ready to be understood, verified, trusted, recommended, and used by AI systems, based on structured inputs (business size, data availability/maturity, technical stack/infrastructure, and goals). Returns a readiness score, tier, gap analysis, priority actions, and a phased implementation roadmap. Deterministic and read-only: it performs no consequential actions and does not guarantee any ranking or recommendation.

Input parameters:

- `businessName` (string): Optional, non-sensitive business name for context.
- `businessSize` (string, required): Size of the business/organization.
- `dataMaturity` (string, required): Availability and maturity of the structured/machine-readable data of the business.
- `goals` (array): One or more readiness goals the business wants to prioritize (1–8, unique values from the enum).
- `industry` (string): Optional industry/category for context.
- `technicalStack` (string, required): Technical stack / infrastructure sophistication.

Output parameters:

- `dimensionScores` (array): Per-dimension breakdown of the overall score.
- `disclaimer` (string): Educational-use disclaimer.
- `engineVersion` (string): Version of the deterministic scoring engine.
- `gapAnalysis` (array): Identified gaps between current and target readiness.
- `implementationRoadmap` (array): Phased implementation roadmap.
- `normalizedInputs` (object): The normalized inputs actually used for scoring.
- `priorityActions` (array): Prioritized recommended actions.
- `readinessScore` (number): Overall AI recommendation readiness score (0–100).
- `tier` (object)
- `tool` (string): Canonical tool identifier.

### `get_ai_readiness_framework` (~82 tokens)

Get AI Readiness Framework

Returns the AI Recommendation Readiness scoring framework: the scored dimensions and their weights, the four readiness tiers with score ranges, and every valid input option (business sizes, data maturity levels, technical stacks, and goals). Read-only and deterministic; use it to understand how the assessment is scored and to build valid inputs for assess_ai_recommendation_readiness.

Output parameters:

- `dimensions` (array)
- `disclaimer` (string)
- `engineVersion` (string)
- `inputOptions` (object)
- `tiers` (array)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/janoliverautomation-stack-canairecommendmybusiness-com/api-mcp#diagnostics

## Score history

- 2026-09-20: 70
- 2026-09-19: 69
- 2026-09-18: 69
- 2026-09-17: 68
- 2026-09-16: 68
- 2026-09-15: 68
- 2026-09-14: 67
- 2026-09-13: 67
- 2026-09-12: 66
- 2026-09-11: 66
- 2026-09-10: 65
- 2026-09-09: 65
- 2026-09-08: 64
- 2026-09-07: 64
- 2026-09-06: 63
- 2026-09-05: 63
- 2026-09-04: 62

## Common questions

### What is the AI Recommendation Readiness Audit | The Black Friday Agency MCP server?

AI Recommendation Readiness Audit | The Black Friday Agency is an MCP server listed in the public MCP registry as io.github.janoliverautomation-stack/canairecommendmybusines…. Can AI confidently recommend your business? The AI Recommendation Readiness Audit shows whether your. This page covers its hosted endpoint (https://canairecommendmybusiness.com/api/mcp).

### Is the AI Recommendation Readiness Audit | The Black Friday Agency MCP server safe to use?

AI Recommendation Readiness Audit | The Black Friday Agency scores 70 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the AI Recommendation Readiness Audit | The Black Friday Agency MCP server expose?

AI Recommendation Readiness Audit | The Black Friday Agency exposes 2 tools: assess_ai_recommendation_readiness, get_ai_readiness_framework. Their descriptions and schemas cost roughly 283 tokens of context every time the server is loaded.

### Does the AI Recommendation Readiness Audit | The Black Friday Agency MCP server require authentication?

No. We connected to AI Recommendation Readiness Audit | The Black Friday Agency without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the AI Recommendation Readiness Audit | The Black Friday Agency MCP server still maintained?

AI Recommendation Readiness Audit | The Black Friday Agency is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://canairecommendmybusiness.com/api/mcp
- Website: https://canairecommendmybusiness.com/
- Changelog RSS feed: https://verifymcp.io/servers/janoliverautomation-stack-canairecommendmybusiness-com/api-mcp.xml
- Changelog JSON feed: https://verifymcp.io/servers/janoliverautomation-stack-canairecommendmybusiness-com/api-mcp.json
- HTML version of this page: https://verifymcp.io/servers/janoliverautomation-stack-canairecommendmybusiness-com/api-mcp