The problem isn’t the CRM. It’s the half-day of research before the first call.
Enterprise sellers rarely lose deals because they lack a system of record. They lose them because, by the time they’ve manually pieced together who an account is, what it cares about, who the real buyer is, and why now is the moment to reach out, the window has closed \u2014 or a faster competitor has already had the conversation.<\/p>\n
Reps routinely spend hours each week toggling between LinkedIn, company websites, news searches, and analyst reports just to assemble a single account brief. And even when the work is done, generic firmographics \u2014 employee count, revenue, industry \u2014 tell a seller who a company is, not what it is prioritizing, what it is spending on, or why it would buy now.<\/p>\n
The Microsoft Dynamics 365 Sales Qualification Agent already removes the busy work by automatically following up, qualifying and delivering sellers researched leads the moment the lead is created and qualified. Draup augments this research with deep, account specific intelligence delivered automatically.<\/p>\n
What Draup is
Draup is an AI-driven sales intelligence platform that aggregates firmographic, technographic, workforce, and executive data across millions of companies globally. Its intelligence is purpose-built for enterprise sellers who need to understand a prospect’s technology landscape, business priorities, spending patterns, and decision-making structure before the first conversation \u2014 not weeks into the cycle.<\/p>\n
Why we built on MCP
Draup exposes its intelligence layer through a Model Context Protocol (MCP) server, which makes it natively compatible with any AI agent platform that supports MCP tools \u2014 including Microsoft Copilot Studio and, by extension, the Dynamics 365 Sales Qualification Agent.<\/p>\n
That choice matters for sellers and admins alike: because Draup speaks MCP natively, there’s no custom middleware, no brittle point-integration, and no separate login. The Sales Qualification Agent calls Draup the same way it calls any other configured knowledge source \u2014 Draup’s intelligence simply becomes part of the agent’s reasoning.<\/p>\n
How it works inside Dynamics 365 Sales
Microsoft designed the Sales Qualification Agent to be extensible: admins can define custom research insights that instruct the agent to pull from additional knowledge sources or external tools via MCP servers. Each insight has a display name, a natural-language prompt, and a preferred knowledge source. Draup slots in as that source.<\/p>\n
Configuration takes place across two surfaces \u2014 the Dynamics 365 admin settings and Copilot Studio \u2014 in a handful of steps:<\/p>\n
Create a custom research definition in the Sales Qualification Agent and write a natural-language prompt (for example: summarize the company’s current technology stack and estimated IT spend by category, highlighting recent additions, priorities, and outsourcing).
\n Register the Draup MCP server as a connected tool in Copilot Studio and authenticate it with Draup API credentials.
\n Select the Draup MCP tool as the preferred knowledge source back in Dynamics 365, then validate against a known account.
\n Start the agent. From that point on, every lead it processes automatically triggers a call to Draup.<\/p>\n
The enriched output appears under the “Deeper Insights” section of the lead research page \u2014 alongside the agent’s standard account and competitor research \u2014 automatically, for every single lead, with no extra step for the seller.<\/p>\n
What sellers actually see
Draup doesn’t stop at describing an account; it reasons about fit. A few representative examples of what surfaces directly on the lead research page:<\/p>\n
A structured breakdown of an account’s technology stack, recent additions, security posture, and estimated IT spend \u2014 synthesized into a few readable paragraphs a seller can absorb in under a minute.
\n An account’s strategic priorities, framed explicitly in terms of what the seller’s own company could offer.
\n A single fit assessment for large, complex accounts \u2014 combining scale indicators, current initiatives, and investment areas to surface where an offering is most likely to land.<\/p>\n
Behind these insights is a library of MCP tools, each scoped to a specific type of intelligence \u2014 company details and financials, tech stack and IT spend, workforce trends, job postings, executive movement, strategic priorities, investments, M&A activity, and news signals \u2014 configured per the custom insights a team defines.<\/p>\n
The payoff
For sellers: open a lead and get a researched, prioritized account brief instantly \u2014 not a generic firmographic snapshot.<\/p>\n
For sales leaders: every rep qualifies leads with the same depth of insight as your best researcher \u2014 consistently, at scale.<\/p>\n
For the Microsoft ecosystem: a native, MCP-based extension that makes the Sales Qualification Agent smarter out of the box, with no new integration pattern to maintain.<\/p>\n
What’s next
Today the integration covers account profiling and trigger outreach. The same architecture \u2014 a Draup MCP tool, a natural-language prompt, a preferred knowledge source \u2014 extends cleanly to the rest of the seller motion: discovering net-new ICP accounts, scoring opportunities against a product catalog, recommending specific buyers by role change, and surfacing competitive displacement and timing signals through the deal cycle. The roadmap is shaped directly by what Microsoft and early customers find most valuable in production.<\/p>\n
Draup is available on the Microsoft Marketplace<\/a>. To scope a pilot or expand the tool library, reach out to the Draup team ([email\u00a0protected]<\/a>). <\/p>\n About Draup
Draup is an AI-driven sales intelligence platform that aggregates firmographic, technographic, workforce, and executive data across millions of companies globally. Its intelligence is purpose-built for enterprise sellers who need to understand a prospect’s technology landscape, business priorities, spending patterns, and decision-making structure before the first conversation \u2014 not weeks into the cycle.<\/p>\n
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