.png){kind=logo}
Improvado's MCP server connects Gong call data to AI agents. Surface deal risks, analyze rep talk tracks, track competitive mentions, and review pipeline health — all in plain English. Works with Claude, ChatGPT, and any MCP-compatible tool.
Your AI agent becomes a direct line to Gong intelligence. Ask about competitor mentions, objection patterns, deal health signals, or rep coaching needs — the MCP server queries call transcripts and metadata at scale.
Your AI agent reads harmonized data across 500+ platforms. "Cost" in Google Ads and "spend" in Meta Ads resolve to the same field automatically.
Your AI agent can push Gong-derived insights back to your CRM. Summarize calls, add next steps, flag deal risks, and update opportunity fields — without switching tools or copy-pasting notes.
250+ governance rules enforce naming conventions, budget limits, and KPI thresholds. SOC 2 Type II certified.
Your AI agent watches for deal risk signals — no next step set, competitor mentioned, decision-maker went silent — and surfaces them before the forecast call. Coaching gaps surface automatically, not at the end of the quarter.
Automated weekly reports, anomaly flagging, and budget alerts — all from a single conversation. No more morning check-ins across 5 dashboards.
Your AI agent can push Gong-derived insights back to your CRM. Summarize calls, add next steps, flag deal risks, and update opportunity fields — without switching tools or copy-pasting notes.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
Pipeline reviews happen every week. Managers ask reps about deal health, and reps recall what they want to share. Nobody has time to re-listen to calls. Forecast accuracy suffers because deal signals stay in the recordings, not in the conversation.
Improvado's MCP server lets your AI agent query Gong call transcripts for every deal in the pipeline. Before the forecast meeting, surface actual call signals — competitor mentions, objections, champion engagement — without anyone re-watching a recording.
A new competitor is gaining traction. You know it's coming up on calls, but to understand how reps respond and where deals are being lost, someone has to manually search Gong, filter by competitor name, listen to relevant clips, and synthesize findings. That's a week of work.
Ask your AI agent to analyze all calls mentioning a specific competitor across the entire team. The MCP server surfaces mention frequency, deal stages where the competitor comes up, how reps responded, and which responses correlated with wins vs. losses.
New reps need call examples — specifically, great discovery calls, objection-handling moments, and closing sequences. Finding the right clips means asking a manager who has to remember which calls were good, search Gong, and share links manually. It doesn't scale.
Your AI agent queries Gong for calls matching specific criteria — high engagement, specific objection types, particular stages. Surface the best examples automatically and give new reps a curated library without any manual curation effort.
Same MCP connection, different workflows for every team member. Agency CEOs get portfolio health. Media Strategists get campaign QA. Analysts get cross-platform reports. Account Managers get auto-generated QBR decks. Creative Directors get performance-based briefs.
Each role asks in natural language. The MCP server handles the complexity — rate limits, auth, schema normalization, governance — behind the scenes.
Call transcripts and recordings, call metadata (duration, participants, deal associations), deal intelligence signals (topics, trackers, next steps), rep performance metrics (talk ratio, engagement score, response times), and team-level call analytics. Essentially everything in the Gong API, queryable in natural language.
Yes. You can search across all transcripts for specific keywords, topics, objections, competitor mentions, or phrases. The MCP server queries Gong's transcript index and returns relevant excerpts with call context — deal name, rep, stage, and date.
Yes. The MCP server uses your Gong API credentials and respects all existing permission scopes. If a rep's calls are restricted to managers only, the MCP integration enforces the same restriction. No data is accessible beyond what the authenticated user's permissions allow.
Gong's native AI features work within the Gong interface. Improvado's MCP server brings Gong data into any AI tool you use — Claude, ChatGPT, Cursor, or your own agent. It also lets you combine Gong call insights with CRM data, marketing attribution, or product usage in one query, which Gong's UI doesn't support.
The Gong MCP integration accesses transcript and call data through Gong's official API using your organization's credentials, and data is transmitted over encrypted connections. No call content is stored by the integration layer beyond what is needed to respond to the immediate query. Access to specific calls and transcripts is governed by Gong's own permission model — users with restricted access in Gong will not have those calls exposed through the MCP integration either.
Through the Gong MCP integration, an AI agent can analyze talk-to-listen ratios, extract key topics and competitor mentions from transcripts, summarize call outcomes, track how often specific objections arise across a set of calls, and identify coaching opportunities by rep. You can ask questions like 'which deals had the most pricing objections last month' or 'summarize the discovery calls from this week' without manually reviewing each recording. This significantly accelerates call review workflows for sales managers and revenue operations teams.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
.png)
