Clozd MCP
Clozd MCP is an open standard protocol that securely connects real-time customer feedback data to AI tools like ChatGPT or Claude, enabling sales and GTM teams to integrate authentic buyer insights into their existing workflows through a simple four-step setup and curated prompts for competitive analysis, objection handling, demo evaluation, and no-decision recovery.
AI is changing how businesses make decisions—but it’s only as powerful as the data behind it. With the Clozd MCP, your AI workflows are now grounded in real customer truth.
Model Context Protocol: Connect your data to AI
MCP is an open standard that allows AI tools to safely access live external data. Think of it as a secure bridge between Clozd and your AI assistant. Clozd MCP makes real buyer feedback available inside the tools your team already uses.
Connect in Four Easy Steps
- 1.Pick your AI tool
Choose a client you'd like to use—Claude, ChatGPT, Windsurf, Gemini, or another AI assistant. - 2.Add the Clozd MCP server
Contact your AI admin to add the Clozd MCP—so you can connect and securely access your customer feedback. - 3.Sign in with your identity provider
Authorize with your identity provider. Your admin scopes which programs the AI tool can see. - 4.Start asking questions
Connect your customer insights with the everyday tools your team and agents already use.
You're Connected—Now Let's Get Started
Try these curated prompts to help every GTM team get value from Clozd MCP from day one.
Sales
- Competitive prep in minutes: Summarize the top reasons we lost to our top competitor set in the last 90 days and pull two representative customer quotes I can use in prep.
- Objection pattern review: Which objections come up most often during evaluation, and which ones correlate most strongly with losses? Include examples and suggested talk tracks.
- Demo quality readout: Pull buyer quotes about demo quality and summarize what the best demos had in common versus the ones that failed to build confidence.
- No-decision recovery scan: List deals marked “no decision” and summarize the common reasons buyers stalled, delayed, or walked away.
- Sales execution audit: Which deals cite sales responsiveness or follow-through as a positive factor, and what specifically did reps do that built confidence?
- Lost-momentum review: Which deals cite sales responsiveness or follow-through as a negative driver, and what specifically went wrong in the process?
- Price ceiling moments: Find examples of pricing resistance involving finance or procurement and summarize the thresholds or concerns buyers mentioned.
- Evaluation activity analysis: Which sales activities—like demos, pricing calls, or technical deep dives—are mentioned most positively by buyers, and why?
Marketing
- Messaging gap scan: What messaging gaps appear most often in recent interviews, and which competitor narratives seem to benefit from them?
- Pricing theme breakdown: How does pricing show up in losses? Break it into themes like too expensive, packaging friction, budget freezes, and unclear ROI.
- Decision maker analysis: Summarize buyer perceptions of our positioning and brand, then show which personas most often act as decision-makers versus influencers.
- Packaging friction review: Summarize buyer feedback on packaging and add-on structure, and explain how it affects evaluation momentum and deal outcomes.
- Industry message map: Which deals cite sales responsiveness or follow-through as a positive factor, and what specifically did reps do that built confidence?
- Standalone vs. suite narrative: Summarize why buyers choose all-in-one platforms versus standalone solutions, and identify which narrative appears to resonate most often.
- Outcome proof extraction: Extract the strongest customer proof points from buyer feedback, including time saved, risk reduced, revenue impact, and outcomes that support messaging.
- Trend monitor: What buyer themes have increased in frequency this quarter, and which should shape the next messaging update or campaign narrative?
Customer Success (CS)
- Renewal risk signal scan: Summarize the top themes in at-risk renewals and highlight the earliest warning signs CS teams should watch for.
- Onboarding friction review: What implementation or onboarding issues come up most often, and which appear to have the biggest downstream impact on satisfaction or retention?
- Expectation gap analysis: Find examples where expectations set during the sales process did not match the post-sale experience—and then group those gaps into clear themes.
- Adoption blocker summary: Which product, process, or team-related blockers most often slow adoption after kickoff, and how do customers describe the impact?
- Expansion finder: Identify accounts where customers express unmet needs, adjacent use cases, or positive momentum that could indicate expansion opportunities.
- Value realization evidence: Pull customer quotes showing measurable value, successful outcomes, or meaningful wins that I can use in renewal prep or executive reviews.
- Churn driver breakdown: Summarize the top reasons customers churn, separate preventable from non-preventable themes, and call out the patterns that appear most often.
- QBR prep from customer voice: Summarize what [insert segment] cares about most, where they see value and experience friction. Include quotes that strengthen QBR narrative.
Product
- Product gap summary: Identify the most common product capability gaps mentioned in losses and group them into themes with representative examples.
- Ease-of-use signal review: Show where buyers describe the product as intuitive versus complex, and summarize which workflows or features drive those perceptions.
- Integration and API pressure test: Which integrations are requested most often, which missing integrations are tied to loses, and what do buyers say about the API experience?
- UI and UX impact review: Summarize buyer feedback on the user experience and whether it helps outcomes, slows adoption, or creates confusion.
- Reporting sentiment: Pull buyer quotes about reporting, exports, and access to customer data, then summarize the sentiment behind each theme.
- Feature perception: Which features are praised most often, and which receive the most criticism? Group them by theme and frequency.
- Win-side strengths: What product strengths most often contribute to wins, and which buyer quotes best explain the value behind those decisions?
- Loss-side product drivers: What product-related factors contribute most often to losses, and which themes appear most urgent for roadmap or enablement attention?
Executive
- Quarterly theme brief: Compare win drivers versus loss drivers from the last six months and identify the biggest gaps we should address first.
- Change-over-time review: Summarize how loss themes changed in the last three months compared to the prior three months, and highlight any emerging themes.
- High-value deal inspection: Show the largest deals we won and lost in the last year, summarize the decisive factors in each outcome, and flag patterns leadership should act on.
- Segment win-rate breakdown: Break down win rate by segment and highlight where we see the strongest drivers, weakest drivers, and clearest path to improvement.
- Decision-driver leaderboard: Show the top ten most-cited decision drivers overall, including frequency, direction, and a representative quote for each.
- Expansion and retention scan: What are the top drivers of retention, churn, and expansion? Separate value realized, new use cases, and packaging themes.
- Regional and tier performance: Are there specific company tiers or regions where we lose more often? Break down outcomes and summarize the main drivers behind them.
- Sales cycle pressure test: What is the average sales cycle length for wins versus losses, and which drivers correlate most strongly with longer cycles?
Available Tools
Here’s what you can access with Clozd MCP:
- Programs & win rates: Start with your available Clozd programs, then measure win-loss performance across them.
/get_programs/get_win_rates
- Deals & responses: Pull deal records, customer responses, summaries, and transcripts.
/get_deals/get_responses/get_response_summaries/get_transcripts
- Decision Drivers: See what drives wins and losses—including themes, sentiment, supporting quotes, and trend counts.
/get_decision_drivers/get_decision_driver_counts/get_decision_driver_categories/get_decision_driver_category_counts/get_driver_quotes
- Competitive insights: Track competitor frequency and understand which factors help or hurt against specific competitors.
/get_competitors/get_competitor_sentiment_drivers
- Gong signals: See what Gong conversations reveal and compare those patterns with the drivers identified in Clozd interviews.
/get_gong_drivers/get_gong_driver_counts/get_gong_driver_categories/get_gong_driver_category_counts/get_gong_driver_overlap
- Tags & metadata: Use tags, deal associations, usage trends, and flagged deal types (like win-back opportunities) to add more context to your analysis.
/get_tags/get_awe_deals
FAQs
Can I access multiple Clozd programs at once?
Yes. The Clozd MCP can pull data from any programs within an organization. The customer will need to specify from which programs data should be queried. Data is pulled from one program at a time.
Do my Clozd role permissions carry over to the MCP?
Yes. Role-based permissions set in the Clozd Platform apply directly to MCP access. If a user can only view certain programs or data in Clozd, those same restrictions are enforced through the MCP connection—with no additional configuration required.
Is Clozd MCP audit-ready for enterprise security teams?
Yes. Connections, sessions, and access events are logged for security review. Authentication runs through OAuth 2.0 and SSO—no API keys, no local credentials. Clozd MCP is built to meet enterprise security expectations out of the box.
Can I add MCP to providers besides those listed above?
Yes. MCP is an open standard, so any AI tool or platform that supports custom MCP connections can connect to it. The Clozd MCP server is not limited to the AI tools listed above.
Clozd MCP
The truth layer for your AI tools.
Related
Clozd MCP: Customer truth for your AI workflows
Clozd MCP (Model Context Protocol) is an open standard that securely integrates verified customer feedback from the Clozd Platform into existing AI tools like ChatGPT and Claude, enabling businesses to ground their AI-driven decision-making workflows in accurate, real-time customer insights rather than assumptions, thereby improving decision speed and reducing friction for teams such as CROs and CMOs.
Trella Health Uses Win-Loss Insights to Refine Product Strategy and Improve Sales Training
Trella Health initiated a three-month pilot win-loss analysis program with Clozd in mid-2024 to understand their low CRM product win rate, which led to expanded use across departments, improved sales coaching, validated strategic assumptions, increased cross-functional engagement, and fostered a customer-centric company culture.
Unlock Rich Customer Feedback With Live Interviews
The article explains how Clozd's expert-led live interviews provide rich, nuanced customer feedback by conducting strategic, in-depth conversations that capture motivations and perceptions beyond surveys, with insights transcribed and analyzed in their AI-powered platform to inform better business decisions, exemplified by their effective use in win-loss analysis.
Launching Win-Loss Analysis: A Sales Team FAQ & Implementation Guide
The article explains that win-loss analysis is a strategic B2B process of gathering direct buyer feedback to understand why sales opportunities are won or lost, enabling companies to improve product offerings, competitive positioning, sales training, messaging, pricing, and packaging, ultimately increasing win rates and informing leadership decisions without focusing on individual salesperson performance.
Clozd for Revenue Leaders: Real Buyer Insights for Revenue Growth
Clozd provides revenue leaders with authentic buyer feedback that enables them to increase win rates, recover lost revenue, and make smarter go-to-market decisions by uncovering key factors behind wins, losses, and hidden revenue opportunities, as demonstrated by companies like Gong, Nitrogen, and StackAdapt.
Clozd Platform Overview
Clozd is an AI-powered platform that automates the collection of authentic customer feedback through workflows and interviews, rapidly analyzes unstructured data with transcription, summarization, thematic aggregation, and tagging, and delivers actionable insights in real-time via integrations with communication and CRM tools to inform critical business decisions.