# AI Capability Rollout Framework (remote · airolloutframework.com)

90-day AI adoption framework for managers: overview, pricing, FAQ and an AI readiness assessment.

- Trust score: 67/100 (medium)
- Change this week: +4
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-28

## Components

- remote · `airolloutframework.com`: 67/100 (this document), [markdown](https://verifymcp.io/servers/com-airolloutframework-ai-rollout-framework/airolloutframework.md), [page](https://verifymcp.io/servers/com-airolloutframework-ai-rollout-framework/airolloutframework)

## Channel facts

- Endpoint: `https://airolloutframework.com/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 2026-09-28.

- **Endpoint Security**: 63/100
  - 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 5 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.
  - The HSTS (Strict-Transport-Security) header is present.
  - 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**: 66/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 1414 tokens (~282/item across 5 items; 5 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 23/100
  - Stability observed for 7 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.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 5 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 Capability Rollout Framework MCP server?

AI Capability Rollout Framework is a hosted endpoint at https://airolloutframework.com/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 com-airolloutframework-ai-rollout-framework 'https://airolloutframework.com/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "com-airolloutframework-ai-rollout-framework": {
      "url": "https://airolloutframework.com/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "com-airolloutframework-ai-rollout-framework": {
      "type": "http",
      "url": "https://airolloutframework.com/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.com-airolloutframework-ai-rollout-framework]
url = "https://airolloutframework.com/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-airolloutframework-ai-rollout-framework": {
      "type": "remote",
      "url": "https://airolloutframework.com/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add com-airolloutframework-ai-rollout-framework --url 'https://airolloutframework.com/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  com-airolloutframework-ai-rollout-framework:
    url: "https://airolloutframework.com/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "com-airolloutframework-ai-rollout-framework": {
      "Transport": "http",
      "Url": "https://airolloutframework.com/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add com-airolloutframework-ai-rollout-framework -t streamable-http -u 'https://airolloutframework.com/mcp'
```

### Other

```json
{
  "mcpServers": {
    "com-airolloutframework-ai-rollout-framework": {
      "type": "http",
      "url": "https://airolloutframework.com/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.

### 2026-09-28 (score 67, +1)

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

### 2026-09-26 (score 66, +1)

- [security] Tool “get_pricing” rewrote its description, which is the text the model reads

### 2026-09-25 (score 65, 0)

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

### 2026-09-24 (score 65, +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.

### 2026-09-22 (score 64, +1)

- [functional improvement] Stability: unverified → 0.03

### 2026-09-21 (score 63)

First indexed and scored.

## MCP tools (5)

### `get_framework_overview` (~38 tokens)

Get the AI Capability Rollout Framework's three implementation phases, four capability pillars, and core positioning statement. Read-only, no authentication required.

### `get_pricing` (~70 tokens)

Get current pricing and checkout URLs for the AI Capability Rollout Framework ($99 one-time), the Framework + Executive Suite bundle ($199 one-time, or a $100 upgrade for existing framework owners), and The Complete AI Learning Path team-training bundle ($24.99/user). Read-only, no authentication required.

### `get_faq` (~116 tokens)

Get frequently asked questions about the AI Capability Rollout Framework, covering pricing, governance, and implementation topics. Read-only, no authentication required.

Input parameters:

- `topic` (string): Optional filter. Use a category for reliable results: "assessment", "implementation", "governance", "measurement", "concepts", "pricing", or "products". Any other value falls back to a free-text sear…

### `search_knowledge_base` (~59 tokens)

Search the AI Rollout Framework knowledge base (methodology, definitions, positioning, changelog) for a keyword or phrase. Returns matching sections with links to the full source document.

Input parameters:

- `query` (string, required): Keyword or phrase to search for.

### `assess_ai_readiness` (~1131 tokens)

Run the AI Capability Rollout Framework's 16-question AI Readiness Score assessment on behalf of a user and return their readiness stage with a recommended next step. Ask the user each of the 16 questions (or use their existing answers) and rate each response 1-5 (1 = Strongly Disagree ... 5 = Strongly Agree), then call this tool with all 16 answers. Returns the stage name and recommendation text only — the same kind of result a user gets on the website, without a numeric score or scoring breakdown. Read-only, no authentication required.

Input parameters:

- `q1` (integer, required): Leadership has discussed how AI may affect workflows, productivity, or service quality in our environment. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q10` (integer, required): People here could describe at least one current task that AI could meaningfully assist without major risk. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q11` (integer, required): There is at least some awareness of how AI tool outputs should be reviewed before they affect real work. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q12` (integer, required): If we piloted AI in one area today, we could define what success looks like in practical terms. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q13` (integer, required): Most people here could use a basic AI tool with at least some practical confidence. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q14` (integer, required): There is some shared understanding of what AI is - and is not - good at in a workplace context. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q15` (integer, required): People here feel comfortable asking questions about AI without fear of looking uninformed. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q16` (integer, required): If a structured AI skill development path existed for our team, there would be genuine interest in using it. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree…
- `q2` (integer, required): There is at least a basic understanding of why AI would be used here beyond general curiosity. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q3` (integer, required): Someone is clearly responsible for evaluating AI opportunities or next steps. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q4` (integer, required): AI discussion here is tied to outcomes, workflows, or risks rather than hype. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q5` (integer, required): People generally understand what data should never be entered into public AI tools. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q6` (integer, required): AI use is discussed with at least some awareness of policy, compliance, or reputational risk. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q7` (integer, required): Important AI outputs would be reviewed before they are acted on or shared broadly. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q8` (integer, required): There is at least a basic sense of what "safe experimentation" with AI looks like here. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)
- `q9` (integer, required): We can identify at least one low-risk workflow where AI could improve speed, quality, or consistency. (Rate 1-5: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/com-airolloutframework-ai-rollout-framework/airolloutframework#diagnostics

## Score history

- 2026-09-28: 67
- 2026-09-27: 66
- 2026-09-26: 66
- 2026-09-25: 65
- 2026-09-24: 65
- 2026-09-23: 64
- 2026-09-22: 64
- 2026-09-21: 63

## Common questions

### What is the AI Capability Rollout Framework MCP server?

AI Capability Rollout Framework is an MCP server listed in the public MCP registry as com.airolloutframework/ai-rollout-framework. 90-day AI adoption framework for managers: overview, pricing, FAQ and an AI readiness assessment. This page covers its hosted endpoint (https://airolloutframework.com/mcp).

### Is the AI Capability Rollout Framework MCP server safe to use?

AI Capability Rollout Framework scores 67 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 Capability Rollout Framework MCP server expose?

AI Capability Rollout Framework exposes 5 tools: get_framework_overview, get_pricing, get_faq, search_knowledge_base, assess_ai_readiness. Their descriptions and schemas cost roughly 1,414 tokens of context every time the server is loaded.

### Does the AI Capability Rollout Framework MCP server require authentication?

No. We connected to AI Capability Rollout Framework without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the AI Capability Rollout Framework MCP server still maintained?

AI Capability Rollout Framework is still listed as active in the MCP registry. We last reached this channel on 28 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://airolloutframework.com/mcp
- Website: https://airolloutframework.com/
- Changelog RSS feed: https://verifymcp.io/servers/com-airolloutframework-ai-rollout-framework/airolloutframework.xml
- Changelog JSON feed: https://verifymcp.io/servers/com-airolloutframework-ai-rollout-framework/airolloutframework.json
- HTML version of this page: https://verifymcp.io/servers/com-airolloutframework-ai-rollout-framework/airolloutframework