Home / Companies / Vespa / Blog / Post Details
Content Deep Dive

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

Blog post from Vespa

Post Details
Company
Date Published
Author
Eivin Bingen
Word Count
3,891
Company Posts That Month
2
Language
English
Hacker News Points
-
Post removed?
No
Summary

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.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
MCP 56 2,241 148 72 -74%
LLM 31 747 162 79 -85%
AI Agents 2 931 231 103 -84%
Observability 1 472 102 54 -85%
RAG 1 101 30 23 -91%
Vector Search 1 265 57 33 -89%
Use This Data

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.