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AgentVoice – Get feedback from AI to improve your MCP

AgentVoice – Get feedback from AI to improve your MCP

by KenRuf·Feb 25, 2026·1 point·0 comments
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AI Analysis

●●SolidBig BrainSolve My Problem

Catches silent agent failures that human logs miss, but needs working demo beyond landing page.

Strengths
  • •Uniquely triangulates three signals (LLM analysis + telemetry + agent feedback) to surface friction humans never report
  • •Solves real MCP pain: agents silently fail on enum constraints, case sensitivity, undocumented schema details
  • •Agent-submitted feedback mechanism is clever—lets the consumer directly narrate their own friction
Weaknesses
  • •Landing page is blank (Lovable project not published) — can't assess actual product quality or implementation
  • •No open-source code, pricing model, or live demo visible; unproven at scale beyond single 10-minute trace
Target Audience

API and MCP server maintainers shipping agent-facing systems

Similar To

LogRocket (session replay) · Datadog APM (observability) · Sentry (error tracking)

Post Description

I wanted to share a tool we built to solve a specific frustration: AI agents (like Claude Code or Cursor) are becoming the primary consumers of our APIs, but they are "silent" users. Unlike human developers who file GitHub issues or post on Discord when a schema is confusing or an error message is cryptic, agents just fail, retry, or give up.

We ran a trace on our own MCP server and found 9 distinct friction points in a single 10-minute session. Things like undocumented enum constraints and case-sensitivity issues that never showed up as "errors" in our standard logs.

AgentVoice closes this loop by triangulating three sources: it runs an LLM observer over session transcripts to diagnose intent, pulls production telemetry to prove the scale of the failure, and adds a submit_feedback tool so agents can narrate their own friction in real-time.

I’d love to get feedback on the approach, especially from anyone currently shipping MCP servers or agent-facing APIs.

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