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Improvado connects Wrike to Claude, ChatGPT, and any MCP-compatible AI agent. Query project health, task completion rates, team workload, and time tracking data in plain English — no manual report exports required.
Stop manually navigating Wrike dashboards and exporting reports. Ask your AI agent for overdue tasks by owner, project completion rates, workload distribution, or billable hour summaries — across any folder, project, or time period.
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 doesn't just read Wrike data — it acts on it. Update task statuses, reassign work, create subtasks from templates, and bulk-edit project timelines through natural language.
250+ governance rules enforce naming conventions, budget limits, and KPI thresholds. SOC 2 Type II certified.
Set up watches on the project metrics that matter. Your AI monitors Wrike continuously and flags overdue task accumulation, workload imbalances, and projects at risk of missing their deadline.
Automated weekly reports, anomaly flagging, and budget alerts — all from a single conversation. No more morning check-ins across 5 dashboards.
Your AI agent doesn't just read Wrike data — it acts on it. Update task statuses, reassign work, create subtasks from templates, and bulk-edit project timelines through natural language.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
Weekly project status reports require opening every active project in Wrike, checking task completion percentages, summarizing blockers, and pasting everything into a doc. With 15+ active projects, this takes 2+ hours every Friday — time that adds zero value.
Improvado extracts project and task data from Wrike into a queryable model. The MCP server lets your AI generate a complete status report in seconds — completion rates, overdue tasks, owner summaries, and risk flags across all projects.
Over-allocation isn't visible until a team member misses a deadline or raises it in a 1:1. Wrike has workload views, but manually checking each person's capacity and comparing it to upcoming task due dates across multiple projects isn't done proactively.
Improvado normalizes Wrike task assignment and estimated effort data into a structured model. The MCP server lets your AI surface workload imbalances before they cause delays — flagging over-allocated team members and suggesting rebalancing.
Wrike captures time entries, but almost nobody analyzes them. The data sits unused because turning it into meaningful insights — billable hours by project, estimated vs actual effort, most time-intensive task types — requires custom report building.
Improvado normalizes Wrike time tracking data alongside project and task metadata. The MCP server lets your AI analyze actual vs estimated hours by project, identify consistently underestimated task types, and surface billable hour summaries on demand.
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.
Tasks (status, assignee, due date, custom fields, subtasks), projects and folders, time tracking entries, workload and capacity data, project templates, comments, and attachments metadata. Both Wrike Business and Wrike Enterprise configurations are supported.
Both. Read operations include all project, task, and time tracking analytics. Write operations include creating and updating tasks, reassigning work, changing statuses, creating projects from templates, and managing subtasks. Permissions are scoped to your Wrike API credentials.
Yes. The MCP server preserves custom field values and workflow status configurations when extracting Wrike data. Your AI can query by custom field values, filter by workflow stage, and update custom fields through write operations.
Any MCP-compatible client — Claude Desktop, ChatGPT, Cursor, Windsurf, Gemini, and custom applications using MCP HTTP transport. Claude is the most commonly used due to native MCP support.
Wrike's native analytics are dashboard-based and require you to know which report to build. The MCP server lets you ask any question in plain language, combine Wrike data with data from other tools, and surface insights that aren't available in Wrike's reporting UI.
If you're already an Improvado user, connect Wrike in the integrations panel and start querying at app.improvado.io/agent. For Claude Desktop or Cursor, add one line to your MCP config — under 60 seconds.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
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