Deploy, Discover, Inspect, Observe: A Summer Spent Making a Public Vespa MCP Server

Four Vespa interns developed a standalone, publicly hosted Model Context Protocol server that enables AI assistants such as Claude and Codex to deploy, inspect, discover, monitor, and troubleshoot Vespa Cloud applications without requiring local installation or an application-specific server. The project emphasizes careful MCP tool design, using intuitive parameters, concise responses, filtering, summaries, and informative errors to reduce agent mistakes and context costs, while adding capabilities such as direct access to Grafana metrics that are not available through the Vespa CLI. The team addressed protocol limitations involving file uploads and long-running deployments with HTTP upload endpoints, configurable blocking behavior, and plans to adopt newer MCP task features. Authentication works for Vespa Cloud’s Control Plane through Auth0, but secure multi-tenant Data Plane access remains unresolved, limiting the prototype’s production readiness. Evaluations comparing MCP-enabled agents with agents using only a terminal and Vespa CLI found similar ultimate task success rates, but MCP agents required fewer deployment attempts, resolved scenarios more cleanly, and made fewer errors, though tool descriptions and discovery added token overhead. The server is undergoing security review and requires further guardrails and user feedback before a potential public release.

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