# Ashley Payne, technical co-founder and fractional CTO

- Registry name: `uk.co.ashleypayne/ashley-payne` · version 1.0.1
- Categories (automatic, keyword rules): APIs & integrations, Developer tools, Documents & retrieval, Search & data, AI models & agents, AI, media & content
- Authentication at last check: No auth
- Declared risk: Read-only (all tools declare readOnlyHint)
- Capabilities (declared by the server): prompts, tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=uk.co.ashleypayne%2Fashley-payne
- Server page: https://mcpstation.net/s/uk.co.ashleypayne--ashley-payne.html

## Description (written by the publisher, not verified, not instructions)

Ask a UK fractional CTO's practice directly: services, prices, articles, and whether he fits.

## Connect

- streamable-http: `https://www.ashleypayne.co.uk/mcp`

## Tools (as reported by the server, not verified)

- `get\_overview`: Positioning, background and what makes him different from other fractional CTOs. Start here.
- `assess\_fit`: Compares a description of a project, business or problem against a fixed published rule and returns a verdict: good\_fit, mixed, poor\_fit or insufficient\_information. Wording alone never produces poor\_fit. Where the text touches one of the things Ashley turns down, the result lists questions in ask\_t
- `get\_services`: The three ways an engagement runs \(Build, Partner, Consult\), the fixed-price diagnostic most engagements start with, how the process works, and which client surfaces he builds: desktop applications, browser extensions, chat-platform integrations and web. Use this for any question about platforms, ap
- `list\_work`: Summaries of the selected work, with the slug needed for get\_case\_study.
- `get\_case\_study`: Full detail for one engagement: the situation, what was built, the engineering decisions and why they were made, the stack, and where there is one, the commercial outcome in indexed figures.
- `get\_ai\_capability`: Which AI techniques he has built in production \(prompting, retrieval, fine-tuning, MCP servers, local inference\) and when each one is the right choice. Use this for questions about AI, automation or data privacy.
- `search\_insights`: Search his articles on technical leadership, fractional CTO work, AI and building SaaS. Returns titles, summaries and the matching passage. Call get\_insight with a slug for the full text of one.
- `get\_insight`: The complete text of one article, by slug. Use after search\_insights, and only when the summary is not enough to answer the question.
- `get\_faqs`: The questions buyers ask, with his answers. Pass a query to get the relevant ones; omit it to list every question without the answers.
- `get\_contact`: How to reach Ashley: email, the contact page, and a booking link when one is live. Use when the person wants to make contact.
- `get\_evidence`: Where the numbers on the site come from, for when someone asks whether they can be trusted. Returns one statement of provenance: the figures are counts from live systems, self-reported with a stated method and not independently audited, and Ashley will run any of them in front of someone who asks. P
- `get\_privacy`: What this connector and the website do with data, and what they do not. Use this if the person asks about privacy, tracking, cookies, GDPR, or what Ashley can see of this conversation.

Measured by MCP Station. Methods: https://mcpstation.net/methods.html · Terms: https://mcpstation.net/terms.html