Ashley Payne, technical co-founder and fractional CTO
RemoteAbout Ashley Payne, technical co-founder and fractional CTO
Ashley Payne MCP server is a hosted, read-only endpoint for learning about the UK fractional CTO's services, pricing, work and articles. Its project-fit tool returns a verdict and follow-up questions using a consistent server-side rule.
Key features
- 01Read-only practice information
- 02Services, pricing and engagement details
- 03Searchable articles and case studies
- 04Project-fit verdict with follow-up questions
- 05No authentication or installation required
Use cases
- 01Check services, fees and engagement arrangements
- 02Assess whether the practice fits a project
- 03Find relevant case studies and articles
MCP support
Exposes read-only tools and prompts through a Streamable HTTP endpoint, including practice details, fit assessment, case studies, articles, FAQs and contact information. The endpoint requires no authentication.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://www.ashleypayne.co.uk/mcpclaude mcp add --transport http uk-co-ashleypayne-ashley-payne https://www.ashleypayne.co.uk/mcp{"mcpServers":{"uk-co-ashleypayne-ashley-payne":{"type":"http","url":"https://www.ashleypayne.co.uk/mcp"}}}Open in Cursor{"servers":{"uk-co-ashleypayne-ashley-payne":{"type":"http","url":"https://www.ashleypayne.co.uk/mcp"}}}Open in VS Code{"mcpServers":{"uk-co-ashleypayne-ashley-payne":{"type":"http","url":"https://www.ashleypayne.co.uk/mcp"}}}{"mcpServers":{"uk-co-ashleypayne-ashley-payne":{"serverUrl":"https://www.ashleypayne.co.uk/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
12This tool takes no parameters.
Details
From the project READMEAshley Payne MCP server
A remote, read-only MCP server for the practice of Ashley Payne, a UK technical co-founder and fractional CTO. Connect it to your assistant and ask about his services, how an engagement runs and what it costs, his case studies and articles, and whether he suits your project.
- Endpoint:
https://www.ashleypayne.co.uk/mcp - Transport: Streamable HTTP
- Authentication: none
- Registry name:
uk.co.ashleypayne/ashley-payne - Documentation: https://www.ashleypayne.co.uk/ai
This repository holds the description and configuration only. The server is hosted, and the hosted endpoint is the product, so there's nothing to install or run.
What it does
It answers from the same published content as ashleypayne.co.uk, so the assistant and the website can't disagree.
The fit checker is the part that's a tool rather than a brochure. Describe
your situation and it returns a verdict: good_fit, mixed, poor_fit or
insufficient_information. The rule that produces the verdict lives on the
server and is the same for everyone. Your wording on its own never produces a
no. If something you wrote raises a question (do you want him to supply a
delivery team, for instance), it comes back as a question for you to answer,
and only a confirmed answer changes the verdict.
Tools
| Tool | What it returns |
|---|---|
get_overview | The first call: who he is, his background and what sets him apart. |
assess_fit | A verdict on whether he suits your project, with any questions to answer first. |
get_services | Services, prices and how an engagement runs. |
list_work | The case studies, with clients unnamed. |
get_case_study | One case study in full. |
get_ai_capability | How he approaches AI work, including when it isn't the answer. |
search_insights | Search his articles. |
get_insight | One article in full. |
get_faqs | The questions buyers ask, with answers. |
get_contact | Email and the booking link. |
get_evidence | How the figures on the site are counted. |
get_privacy | What happens to what you send the server. |
Prompts
is_he_right_for_me, what_would_this_cost, compare_my_options and
check_the_evidence start the common conversations for you.
Configure it
Claude (web and desktop)
- Open Settings, then Connectors.
- Choose Add custom connector.
- Name it
Ashley Payneand pastehttps://www.ashleypayne.co.uk/mcp. - If it says it can't work out how the server signs in, choose Continue anyway. There's nothing to sign in to.
- Turn it on in a chat from the tools or + menu.
Claude Code
claude mcp add --transport http ashley-payne https://www.ashleypayne.co.uk/mcp
VS Code with GitHub Copilot
Add this to .vscode/mcp.json in your workspace, or to your user MCP
configuration:
{
"servers": {
"ashley-payne": {
"type": "http",
"url": "https://www.ashleypayne.co.uk/mcp"
}
}
}
Codex in the ChatGPT desktop app
Open Settings, then MCP servers, and add a Streamable HTTP server named
ashley_payne with the endpoint above as its URL. Leave the token and header
fields empty, save and restart, then start a new Local Codex chat and
type /mcp to check it's connected. This connects Codex running locally; it doesn't
make the server available in ordinary ChatGPT chats.
Anything else
Any client that speaks Streamable HTTP can connect to the endpoint directly. There's no API key, header or account.
Use it
Ask in your own words. For example:
- "Who is Ashley Payne?"
- "What does he charge, and how does an engagement work?"
- "Has he built anything like our problem before?"
- "How does he decide whether AI is the right answer?"
- "We have developers already. We need one accountable fractional CTO to set direction. Is he a fit?"
The last one will come back with a few questions first. Answer them and ask again.
Privacy
Every tool is read-only. There's no sign-in, no session and no database, and tool arguments aren't logged. Keep personal and confidential details out of the fit checker, because the shape of the problem is enough. The full notice is on the privacy page, in the section on the AI connector.
Contact
Built and run by Ashley Payne Systems Ltd, registered in England and Wales, company number 17463066. [email protected]
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.