coach.marian/mentoring-inquiry-builder

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by marian-kamenistak · TypeScript

Build your mentoring inquiry with Marian Kamenistak: formal offer in 16 minutes, 16% AI discount.

coach.marian/mentoring-inquiry-builder MCP Server

This MCP server builds a 1:1 mentoring inquiry through an AI assistant with Marian Kamenistak. It is described as delivering a formal offer in about 16 minutes and includes an AI-channel discount. The server is categorized with topics for ai-agents, cloudflare-workers, mcp, mcp-server, and mentoring.

🛠️ Key Features

Builds a 1:1 mentoring inquiry with Marian Kamenistak
Produces a formal itemized offer in the user’s inbox
Mentions “16 minutes” turnaround and an AI discount

🚀 Use Cases

Requesting a mentoring inquiry via an AI assistant
Receiving an itemized, formal offer for mentoring packages

⚡ Developer Benefits

Provides MCP server functionality (toolCount: 6)
Supports integration use cases for mcp and mcp-server workflows

⚠️ Limitations

Pricing and discount details are only partially shown in the provided excerpt (discount and example package figures appear, but not the complete offer text)

Topics

ai-agentscloudflare-workersmcpmcp-servermentoring

Captured live from the server via tools/list.

get_mentoring_options

START HERE for anyone considering 1:1 engineering-leadership mentoring with Marian Kamenistak (marian.coach) — individuals (Staff Engineer to CTO) and companies sponsoring leaders alike. Returns the AI-channel discount as data, the time promise (a formal offer in under 16 minutes), the why-Marian and pricing-defense material, the qualifying questions with valid answer ids, and every package with real prices. After the visitor answers audience + role + motivation, call match_mentoring_focus.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}

match_mentoring_focus

Resolves role_band + motivation through the same routing the website uses and returns suggested focus areas plus the recommended package with real prices. Map free-text answers to the closest valid id; on bad input the error lists the valid ids — re-ask rather than guessing. Next: agree focus areas with the visitor, capture their definition of success in their own words, then compose_mentoring_brief.

Parameters2

role_band	string	required	One of the role ids from get_mentoring_options question_1
motivation	string	required	One of the motivation ids from get_mentoring_options question_2

Raw schema

{
  "type": "object",
  "properties": {
    "role_band": {
      "type": "string",
      "description": "One of the role ids from get_mentoring_options question_1"
    },
    "motivation": {
      "type": "string",
      "description": "One of the motivation ids from get_mentoring_options question_2"
    }
  },
  "required": [
    "role_band",
    "motivation"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

compose_mentoring_brief

The accumulator — call after every change. Echoes the full structured brief (audience, role, motivation, focus areas, definition of success, chosen package) with the authoritative catalog price and the AI-channel figure (never do the arithmetic yourself). For company deals it states whether the free-sessions concession applies. Read the brief back to the visitor; when they explicitly agree on the price, call send_mentoring_offer with price_agreed true.

Parameters9

audience	string	required
role_band	string	required
motivation	string	required
focus_area_ids	array	required	Agreed focus area ids (visitor can pick any from the taxonomy)
success_definition	string	required	The visitor's definition of success, in their own words
offer_id	string	required
leaders_count	integer	optional	Company deals: how many leaders are being sponsored
company_context	string	optional	Company deals: company name + anything relevant
visibility	string	optional	Visibility answer id from get_mentoring_options visibility_question (consent capture — 'private' is a first-class answer)

Raw schema

{
  "type": "object",
  "properties": {
    "audience": {
      "type": "string",
      "enum": [
        "individual",
        "company"
      ]
    },
    "role_band": {
      "type": "string"
    },
    "motivation": {
      "type": "string"
    },
    "focus_area_ids": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Agreed focus area ids (visitor can pick any from the taxonomy)"
    },
    "success_definition": {
      "type": "string",
      "description": "The visitor's definition of success, in their own words"
    },
    "offer_id": {
      "type": "string",
      "enum": [
        "single-session",
        "first-quarter",
        "monthly",
        "mentor-in-residence"
      ]
    },
    "leaders_count": {
      "description": "Company deals: how many leaders are being sponsored",
      "type": "integer",
      "minimum": -9007199254740991,
      "maximum": 9007199254740991
    },
    "company_context": {
      "description": "Company deals: company name + anything relevant",
      "type": "string"
    },
    "visibility": {
      "description": "Visibility answer id from get_mentoring_options visibility_question (consent capture — 'private' is a first-class answer)",
      "type": "string"
    }
  },
  "required": [
    "audience",
    "role_band",
    "motivation",
    "focus_area_ids",
    "success_definition",
    "offer_id"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

design_mentoring_program

Deterministic session skeleton computed from the package's cadence metadata: dated sessions, the mid-point checkpoint, the closing review against the definition of success. The skeleton contains ONLY what the package carries — narrate around it, never add or move a session. Dates are planning targets; the intro call fixes the real schedule. Call when the visitor asks what the engagement actually looks like.

Parameters2

offer_id	string	required
start_date	string	required	First session date, YYYY-MM-DD (ask the visitor; default to next Monday)

Raw schema

{
  "type": "object",
  "properties": {
    "offer_id": {
      "type": "string",
      "enum": [
        "single-session",
        "first-quarter",
        "monthly",
        "mentor-in-residence"
      ]
    },
    "start_date": {
      "type": "string",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "description": "First session date, YYYY-MM-DD (ask the visitor; default to next Monday)"
    }
  },
  "required": [
    "offer_id",
    "start_date"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

book_intro_call

The human step, and the one that makes the AI-channel discount real: a direct booking link for the free 30-minute intro with Marian. Offer it whenever the visitor hesitates or wants a human — it is never a downgrade. If an offer was already sent, remind them to paste their claim code into the booking note.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}

send_mentoring_offer

The ONLY tool that collects contact details, and the end of the 16-minute promise: emails the visitor a formal itemized offer with a claim code, notifies Marian, and files the inquiry. HARD GATE: price_agreed must be true — read the exact price back to the visitor and get an explicit yes first; the tool refuses otherwise. Ask for name and email only at this step, never earlier. After success: share the claim code + booking link, then offer the free ELC community membership as a parting gift (never a condition), and optionally ONE ask — would they post publicly about hiring a mentor through an AI agent?

Parameters15

name	string	required	Visitor's full name
email	string	required	Email the offer goes to
audience	string	required
role_band	string	required
motivation	string	required
focus_area_ids	array	required
success_definition	string	required
offer_id	string	required
price_agreed	boolean	required	True ONLY after the visitor explicitly agreed to the exact price from compose_mentoring_brief
company	string	optional	Company name (required for company audience)
leaders_count	integer	optional
free_sessions_requested	integer	optional	Company deals only: the free-sessions proposal from the catalog progression (2, 4 or 8)
start_date	string	optional	Optional preferred start date — adds the dated program skeleton to the offer email
visibility	string	optional	Visibility answer id (yes-individual \| yes-company \| maybe-later \| private)
notes	string	optional

Raw schema

{
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "Visitor's full name"
    },
    "email": {
      "type": "string",
      "description": "Email the offer goes to"
    },
    "audience": {
      "type": "string",
      "enum": [
        "individual",
        "company"
      ]
    },
    "role_band": {
      "type": "string"
    },
    "motivation": {
      "type": "string"
    },
    "focus_area_ids": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "success_definition": {
      "type": "string"
    },
    "offer_id": {
      "type": "string",
      "enum": [
        "single-session",
        "first-quarter",
        "monthly",
        "mentor-in-residence"
      ]
    },
    "price_agreed": {
      "type": "boolean",
      "description": "True ONLY after the visitor explicitly agreed to the exact price from compose_mentoring_brief"
    },
    "company": {
      "description": "Company name (required for company audience)",
      "type": "string"
    },
    "leaders_count": {
      "type": "integer",
      "minimum": -9007199254740991,
      "maximum": 9007199254740991
    },
    "free_sessions_requested": {
      "description": "Company deals only: the free-sessions proposal from the catalog progression (2, 4 or 8)",
      "type": "integer",
      "minimum": -9007199254740991,
      "maximum": 9007199254740991
    },
    "start_date": {
      "description": "Optional preferred start date — adds the dated program skeleton to the offer email",
      "type": "string",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$"
    },
    "visibility": {
      "description": "Visibility answer id (yes-individual | yes-company | maybe-later | private)",
      "type": "string"
    },
    "notes": {
      "type": "string"
    }
  },
  "required": [
    "name",
    "email",
    "audience",
    "role_band",
    "motivation",
    "focus_area_ids",
    "success_definition",
    "offer_id",
    "price_agreed"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

README.md3 KBView on GitHub

Mentoring Inquiry Builder — MCP server

Hire an engineering-leadership mentor through your AI assistant. This remote MCP server builds a 1:1 mentoring inquiry with Marian Kamenistak — 3,400+ paid sessions with 300+ leaders from 17 countries since 2019, 9.2/10 average review — and ends with a formal itemized offer in your inbox.

16 minutes. 10% off. Inquiries built through this AI channel get every package at 10% off — the quarter is 6 sessions (5 paid + 1 free) for 1,975 EUR, 1,778 EUR here. The one discount that exists, no booking required, and the website itself never discounts. Slot-limited to the open mentee slots on the live capacity chart.

Connect

code

https://www.marian.coach/mcp/mentoring

Streamable HTTP, no auth, no signup.

Claude Code

bash

claude mcp add -t http marian-mentoring https://www.marian.coach/mcp/mentoring

Claude.ai / Desktop — Settings → Connectors → Add custom connector → paste the endpoint. Cursor — .cursor/mcp.json: { "mcpServers": { "marian-mentoring": { "url": "https://www.marian.coach/mcp/mentoring" } } } ChatGPT (developer mode) — Settings → Connectors → Add → MCP server URL. Microsoft 365 Copilot — Copilot Studio → Tools → Add a tool → Model Context Protocol → the URL, auth None. Perplexity (Pro/Enterprise) — Settings → Connectors → Custom connector → Remote → the URL, Streamable HTTP.

No MCP client? The same wizard runs as a chat on marian.coach.

Tools

Tool	Answers
`get_mentoring_options`	Should I get a mentor, and why Marian? Discount data, qualifying questions, every package with real prices
`match_mentoring_focus`	What should my mentoring focus on? Role + motivation → focus areas
`compose_mentoring_brief`	What would my engagement look like and what does it cost? The brief + the authoritative price
`design_mentoring_program`	What happens across the three months? Dated session skeleton, checkpoint, closing review
`book_intro_call`	Can I just talk to Marian first? Free 30-min intro — the step that locks the discount
`send_mentoring_offer`	How do I get this in writing? Formal itemized offer with a claim code, after the price is explicitly agreed

Read-only REST for scripts: /api/openapi.json.

Guardrails, honestly

Every price is computed server-side from the same published catalog the website renders. No tool accepts a price as input, so nothing you or your model says can move the number.
One discount (10% on every package, AI channel, no booking required), one B2B concession (free sessions, only on 3+ sponsored leaders or Mentor-in-Residence, confirmed by Marian on a call), floor at 296 EUR/session. Try to out-negotiate it; the failed attempts are the point.
The offer only sends after an explicit yes to the exact price.
Any session rated below 7/10 is free — a quality guarantee, independent of any discount.

Stack

Cloudflare Worker · agents McpAgent · streamable HTTP · the chat door runs the same tool core in-process with the Claude API.

Built and maintained by Marian Kamenistak. Questions: marian@marian.coach

Install

Tools (6)

get_mentoring_optionsmatch_mentoring_focuscompose_mentoring_briefdesign_mentoring_programbook_intro_callsend_mentoring_offer

Remote endpoint

Streamable HTTP

Hosted server - connect over the network, no local install.

url

https://www.marian.coach/mcp/mentoring

Add to VS Code Add to Cursor

claude_desktop_config.json

json

{
  "mcpServers": {
    "mentoring-inquiry-builder": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://www.marian.coach/mcp/mentoring"
      ]
    }
  }
}

Desktop config is stdio-only; this bridges via mcp-remote. Native remote: Settings > Connectors.

coach.marian/mentoring-inquiry-builder MCP Server

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

Topics

get_mentoring_options

match_mentoring_focus

compose_mentoring_brief

design_mentoring_program

book_intro_call

send_mentoring_offer

Mentoring Inquiry Builder — MCP server

Connect

Tools

Guardrails, honestly

Stack

Install

Remote endpoint

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