Returns raw records.
The valueIQ MCP Server connects Claude, Cursor, ChatGPT and any MCP-compatible tool directly to valueIQ, giving you live deals, business cases, and pricing intelligence in every conversation.
The shape of what comes back is the difference between a lookup and a business case.
Returns raw records.
Returns a defensible business case, grounded in your deal context and 2,000+ pricing pages of external competitive data. When your buyer says the competitor is cheaper, your assistant already knows the competitor.
Illustrative examples with fictional data.
Most MCP servers expose your own records. This one runs a methodology against your data and returns intelligence that holds up in a budget conversation.
Ask about a real opportunity by name. Get methodology-grounded next steps, risk calls, and executive-ready framing, scoped to that deal's context.
Business cases, driver assumptions, pricing intelligence, and prior estimates flow into the conversation as structured, cited context.
Every request runs under your own identity and workspace permissions, so your assistant sees exactly what you see.
Ask for any deal by company name and get the value breakdown, each driver's calculated impact, the risks valueIQ sees in the deal, and the readiness assessment from the latest value story.
See which products are ready for deals, read each product's value drivers and equations, check the low, typical and high market figures for a variable, and list deals by stage.
Get the workspace's pipeline rollup, with active deal count, total expected value and a per-stage breakdown, and check how many credits the workspace has left. You can also list earlier coaching threads on a deal.
Ask for a business case for a company and product, and valueIQ creates the deal and generates the customer model. You can also ask for an executive briefing or a sales deck. Generating draws credits.
Create a product from a company website and a product description, then edit its value model: rename drivers, mark them not applicable, or add notes. The last edit can be undone on request. Creating a product draws credits.
List and open a deal's value stories, choose the top drivers and lock a story before a presentation, and read and reply to the customer's comments. You can also see who has been invited to a story and whether they've claimed it.
Describe an objection or a stalled moment, such as price pushback or "good enough", and get a response backed by the deal's quantified value drivers. Follow-up drafts come back for you to review, and nothing is sent for you.
Get structured data from a competitor's published pricing page: tiers, features, billing model and usage metrics, with competitive positioning. Analyses are cached for 90 days, so the data is current but not real time.
Try the Pricing Intelligence Agent →Attach a competitor's value model to a deal and get a side-by-side, driver-by-driver comparison with your own. The competitor's model must already exist in your workspace.
Create a deal, update customer variables such as headcount and recalculate, and log notes and discovery details. Archive deals you've lost and restore them when you need them.
Upload a file such as a discovery call transcript to a deal, so coaching and the customer model can use it. You can list a deal's documents and stop one being used in coaching.
Store a CRM record reference on a deal or product, and read the deal's CRM scorecard: Value Capture, zone, estimated value and the value summary link the CRM displays. CRM integrations can be set up with our team.
Save where a coaching session or multi-step task has got to, then pick it up later or from another client, such as moving from Claude Desktop to Cursor, instead of starting again.
Example prompts are illustrative. Swap in your own deal, company and product names.
MCP (Model Context Protocol) is an open standard for connecting AI tools to live external data. Released by Anthropic in late 2024 and adopted by OpenAI, Google, and Microsoft in early 2025.
Before MCP, using AI for deal work meant copying notes into a prompt and hoping the output fit your situation. MCP eliminates that step: your AI tool connects to your data once and has it available in every conversation: the deal, the value context, the competitive context. No pasting required.
valueIQ's MCP Server is live today. One connection covers Claude, ChatGPT, Cursor, VS Code Copilot, Windsurf and any MCP-compatible client.
Actions the assistant can invoke against valueIQ.
Addressable context the assistant can read on connect.
Named, versioned skills the assistant can adopt.
Before you connect
What teams ask before they connect their AI assistant to valueIQ.
The server, the standard, and the difference.
A remote server at mcp.valueiq.ai that connects Claude, Cursor, ChatGPT and any MCP-compatible tool to the valueIQ value intelligence engine. Once connected, your assistant can read your live deals, generate a business case, coach you through an objection, and pull competitor pricing analysis, without you pasting context into the conversation. It is live, free to connect, and takes about five minutes.
MCP, the Model Context Protocol, is an open standard for connecting AI tools to live external systems. Before it, getting an assistant to reason about a deal meant copying notes into every session and hoping the output fit. With it, the assistant connects once and has the deal, the value model, and the competitive context available in every conversation, inside the tools reps already use.
Most MCP servers hand your assistant records: what was logged, what was said, what was stored. The valueIQ server runs a methodology against your deal and returns something new, a business case with cited equations, an objection response, or a competitor pricing analysis. It is built on 15+ years of B2B SaaS pricing methodology and 2,000+ analysed pricing pages, which is why the numbers hold up when the economic buyer pushes back.
It can draft a document. What it cannot do on its own is build the value model underneath it: which drivers apply to this account, what the defensible benchmarks are, how attribution and execution risk change the number, and what the competitor charges. valueIQ generates that model from methodology, keeps it current as the deal moves, and returns every number with its source attached. The assistant writes better because it is reasoning over a model instead of a guess.
Tools, time, and what you need first.
Claude Desktop, Claude.ai, Cursor, VS Code Copilot, Windsurf, and ChatGPT on Plus, Pro, Business, Enterprise, and Education plans. Any MCP-compatible client works. One connection covers all of them.
About five minutes. Create a free valueIQ account if you do not have one, add mcp.valueiq.ai to your client's MCP settings, and sign in with OAuth the first time your assistant calls a valueIQ tool. There is no token to copy, no IT project, and no admin setup.
No. The server runs on your valueIQ workspace alone. valueIQ integrates with leading CRMs, but no CRM connection is required to get started.
No. Give valueIQ your website and product name and it builds the value model itself: the drivers, the equations, and the market benchmarks. Your assistant is useful on the first deal, including in a market you have never sold into. If you already have a framework, you can put it in and the platform runs on yours.
On the deal, at every stage.
Read your live deals and business cases. Generate a business case for any active deal. Run deal coaching grounded in that deal's own value model. Pull competitor pricing analysis. Create and update deals and their variables. Add a competitor opposition model. Browse your products and market benchmarks. Save a coaching session and pick it up later, in the same client or a different one.
Your assistant answers with the value difference. It has valueIQ's analysis of the competitor's published pricing alongside the business case for this deal, so the rep gets a specific, quantified comparison rather than a generic objection script. The conversation moves from "our price is fair" to "here is what their price buys, and here is what ours delivers for you."
Yes. Before the first call, competitive pricing context and a value hypothesis for the account. In discovery, the initial value model and the questions that sharpen it. In active deals, coaching, objection handling, and business case generation. At renewal, a review of the business case and expansion prep. No minimum deal stage for any capability.
Every value driver carries a cited equation, a market-sourced benchmark, and adjustments for attribution and execution risk. Every variable shows its provenance: a market default, a figure the seller set, or a number the customer confirmed. When your assistant reads back a business case, it reads back the sources with it.
Your data, your scope, what it costs.
Every request runs as you. Reads and most edits run under your workspace's row-level security, so your assistant sees exactly what you see, and the few actions that run on the server check your role and workspace membership first. Authentication is OAuth 2.1 with PKCE and a per-request token; there are no static long-lived credentials. Deal data passed through MCP is never used to train models. Enterprise plans add a full audit log API.
Yes. The MCP Server is included with every plan, including the Free plan with 500 credits a month. Reading deals, coaching, and drafting are free. Generating a deck or creating a deal draws credits at the same rate as the same action in the app. Nothing sends, presents, or publishes on its own; drafts and decks come back to you first.
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