.png){kind=logo}
Improvado's MCP server connects Intercom to AI agents. Query conversation history, ticket volumes, CSAT trends, and customer segments — all in plain English. Works with Claude, ChatGPT, and any MCP-compatible tool.
Stop manually searching conversations to answer leadership questions. Ask your AI agent for ticket volumes, CSAT trends, most common support topics, or individual customer history — the MCP server pulls it from Intercom directly.
Your AI agent reads harmonized data across 500+ platforms. "Cost" in Google Ads and "spend" in Meta Ads resolve to the same field automatically.
Assign conversations, update contact properties, send targeted messages, and manage tags — all through natural language. Your AI agent handles Intercom operations without you opening the inbox.
250+ governance rules enforce naming conventions, budget limits, and KPI thresholds. SOC 2 Type II certified.
Your AI agent monitors Intercom for volume spikes, CSAT drops, SLA breaches, and churn language in conversations. Get notified before support issues escalate or at-risk customers go quiet.
Automated weekly reports, anomaly flagging, and budget alerts — all from a single conversation. No more morning check-ins across 5 dashboards.
Assign conversations, update contact properties, send targeted messages, and manage tags — all through natural language. Your AI agent handles Intercom operations without you opening the inbox.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
CSAT fell 12 points last month. Finding out why means manually reviewing low-rated conversations, tagging themes, cross-referencing assignees and response times, and building a summary. By the time the analysis is done, another month has passed and the underlying issue has grown.
Improvado's MCP server lets your AI agent query all low-CSAT conversations for the period, extract the common themes, identify which teams and topics drove the score down, and generate a root-cause summary — in under 10 minutes.
Customers who are about to churn often signal it in support conversations — mentioning competitor names, asking how to export data, or expressing repeated frustration. But nobody reads every conversation. By the time CS notices a churn risk, the customer has already decided.
Your AI agent scans Intercom conversations for churn signals at scale. It identifies customers using churn language, tags them in Intercom, and alerts your CS team — giving them a window to act before the customer churns.
A product change causes a surge in support tickets. The first sign is the support team complaining they're overwhelmed — hours after the spike started. There's no automated monitoring, so response times deteriorate before anyone adjusts staffing or triggers an engineering response.
The MCP server monitors Intercom conversation volume continuously. When an anomaly is detected — volume spike, new topic category emerging, or SLA breach rate climbing — your AI agent sends an immediate alert with topic breakdown and affected customer segments.
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.
Conversation history and metadata (status, assignee, tags, CSAT scores, response times), contact and company profiles with properties and segments, team performance metrics, article content from the Help Center, and outbound message performance. All queryable in natural language.
Yes. Write operations include sending proactive messages to segments, updating contact and company properties, tagging conversations, assigning conversations to teams, and closing or reopening threads. All write operations require explicit confirmation. Start with read-only access if preferred.
Yes. The MCP server can query Help Center article content, search for gaps between common support topics and existing documentation, and identify which articles need updating based on recent conversation themes.
Yes — this is one of the core advantages of Improvado's MCP server. Cross-reference Intercom conversation data with product usage from Mixpanel or Amplitude, subscription data from your billing system, or CRM deal data. Ask which support topics correlate with churn or which customer segments have the longest resolution times.
Yes, the Intercom MCP integration can retrieve full conversation threads including messages, notes, tags, assignee history, and resolution status, as well as contact and company attributes attached to each conversation. This allows an AI agent to answer analytical questions like identifying which conversation topics have the longest resolution times or which contact segments generate the most inbound volume. Access is scoped to what your connected Intercom workspace and API token permit.
Intercom's built-in reports provide pre-configured charts for team performance, conversation volume, and response times, but are limited to the metrics and filters the Intercom UI exposes. The MCP integration allows you to ask custom analytical questions that go beyond those templates — for example, correlating conversation resolution time with specific product areas mentioned in the thread, or extracting a list of all conversations mentioning a particular issue keyword over a date range. This flexibility is valuable for support operations and product teams who need deeper, ad-hoc insights.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
.png)
