Production Model Context Protocol server so AI agents can read and update live Wrike project data under explicit governance rules.
Production deployment
Live task read/write
DoD drafting
Blocker signaling
Context
PM throughput depended on repetitive status collection and manual tool updates. Project truth lived in Wrike, but keeping it current was human bottleneck work.
Intervention
Built a production Wrike MCP server so agents could read project state, update tasks, prepare draft Definition of Done content, and flag blockers inside the existing PM workspace—with governance constraints on allowed actions.
Outcome
Before: PMs acted as status relays. After: PMs supervise agent output against standards; updates happen in the system of record instead of chat threads and spreadsheets.
System map
Agents act through MCP with constrained write paths; PMs remain accountable for outcomes.
Artifacts
Production MCP server integrated with live Wrike workflows
Machine-checkable patterns for done / blocked / at-risk signaling