Harness FME review: features, pricing, and AI capabilities

Platform overview

Inside FME, Harness ships Release Agent, a multilingual in-app chatbot grounded in Harness documentation and blogs that answers questions on SDKs, flags, targeting, experiment interpretation and cleanup without leaving the UI. AI Summarize condenses feature-flag metric tiles, individual experiment metrics and overall results. Admins toggle both under FME Settings > AI settings.

Across the platform, Harness launched Autonomous Worker Agents in June 2026. They run as governed pipeline steps on customer-controlled Delegates, produce auditable outputs, draw memory from the Harness Knowledge Graph and capability from the Harness MCP.

The MCP server is open source and self-hosted (npx harness-mcp-v2, Docker or from source). It routes 11 consolidated tools to 139 resource types across 30 toolsets, including Feature Management and Experimentation, with 27 pre-built prompt templates. Authentication uses a Harness personal access token, with a documented enterprise SSO path.

For FME specifically, agents can discover projects, list and inspect flags, compare a flag across environments, and find fully rolled-out flags that are safe to remove.