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Improvado's MCP server connects Aha! product data to Claude, Cursor, and any AI agent. Ask about release timelines, feature status, initiative progress, and cross-team dependencies in plain English. No dashboards, no report exports.
Your AI agent becomes a direct window into Aha! product data. Check initiative status, upcoming releases, feature backlogs, and team capacity without switching context. Product intelligence on demand.
Your AI agent reads harmonized data across 500+ platforms. "Cost" in Google Ads and "spend" in Meta Ads resolve to the same field automatically.
Add features, update release dates, change initiative status, and create requirements directly through your AI agent. The Aha! MCP integration turns conversation into product management actions.
250+ governance rules enforce naming conventions, budget limits, and KPI thresholds. SOC 2 Type II certified.
Set up watches on release completeness and initiative velocity. Your AI agent flags features slipping out of a release, initiatives falling behind, and gaps between planned and delivered scope.
Automated weekly reports, anomaly flagging, and budget alerts — all from a single conversation. No more morning check-ins across 5 dashboards.
Add features, update release dates, change initiative status, and create requirements directly through your AI agent. The Aha! MCP integration turns conversation into product management actions.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
Preparing for a roadmap review means pulling data from Aha! into a slide deck: initiative status, feature counts by release, completion percentages. It's a two-hour prep job that happens every two weeks.
Improvado pulls Aha! roadmap data in real time. The AI agent can generate a full roadmap summary — status by initiative, features by release, completion trends — in seconds, directly in the conversation.
Features get added to releases informally throughout the quarter. By the time the sprint planning meeting happens, the release is overloaded — but nobody has a clear picture of how it got there or what to cut.
Improvado tracks Aha! feature-to-release assignments over time. The AI agent can show scope changes, newly added features, and capacity load per release so teams can course-correct before it's too late.
Aha! lives on the product side. Jira lives on the engineering side. Cross-referencing planned features with actual development tickets is a manual reconciliation that rarely happens until something slips.
Improvado connects Aha! and Jira data in the same MCP. The AI agent can match features to tickets, show completion discrepancies, and surface gaps between product intent and engineering execution.
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.
Aha! does not publish an official MCP server. Improvado provides a hosted MCP integration that connects Aha! product data — features, initiatives, releases, and roadmaps — to Claude, Cursor, and other AI tools through a single endpoint.
Features, epics, initiatives, goals, releases, requirements, custom fields, tags, and audit history. All queryable in natural language without writing API queries or exporting reports.
Yes. The Aha! MCP integration supports read and write operations. AI agents can create features, update initiative status, change release assignments, and add notes through the MCP connection.
Yes. Improvado's MCP server connects 500+ platforms including Aha!, Jira, GitHub, and Linear. AI agents can query across product and engineering data in a single conversation — matching features to tickets, comparing planned vs. shipped scope.
Improvado supports multiple Aha! workspaces and product lines in a single connection. Teams with separate roadmaps per product can query across all of them in one request.
Yes. Improvado is SOC 2 Type II certified. API tokens are stored in an encrypted vault and never exposed to the AI model. All queries go through Improvado's secure proxy.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
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