Convai Analytics
Pull Convai session, latency, reliability, usage, and provider telemetry into your agent so you can debug voice or conversational AI quality without living in separate dashboards.
Overview
Convai Analytics is a Grow-phase MCP server that analyzes Convai sessions, latency, reliability, usage, and provider telemetry via your Convai API key.
What is this MCP server?
- Query Convai analytics API with CONVAI_API_KEY for account-scoped metrics
- Session-level analysis plus latency, reliability, and usage views
- Provider telemetry exposure for diagnosing upstream voice or LLM issues
- Optional CONVAI_ANALYTICS_BASE_URL override (default analytics-api.convai.com/v1/analytics)
- npm stdio package @convai/analytics-mcp v0.2.5
- Package version 0.2.5
- Default analytics base: https://analytics-api.convai.com/v1/analytics
- Transport: stdio
What problem does it solve?
Your Convai app misbehaves in production but digging through analytics UIs breaks flow and your agent cannot correlate sessions with latency or provider failures.
Who is it for?
Indie builders shipping Convai-based voice or chat products who want agent-assisted incident triage and usage reviews without manual dashboard hopping.
Skip if: Projects not on Convai or teams that only need generic HTTP logs from their own backend with no Convai account.
What do I get? / Deliverables
After install, your agent queries Convai analytics directly so you get session and reliability answers in the same thread where you fix code.
- Agent-queryable Convai session and usage summaries
- Latency and reliability views for post-release debugging
- Provider telemetry context for root-cause chats
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Journey fit
Post-launch measurement of conversational product quality belongs in Grow when you iterate on retention, reliability, and cost using real session data. Analytics is the canonical shelf for session metrics, latency distributions, and provider-level telemetry rather than building new Convai features.
How it compares
Convai-specific analytics MCP, not application-wide error monitoring like Sentry or a generic SQL analytics skill.
Common Questions / FAQ
Who is Convai Analytics MCP for?
Builders running Convai conversational or voice products who want Claude Code or Cursor to query session, latency, and reliability metrics via API.
When should I use Convai Analytics MCP?
Use it in Grow after launch when you debug reliability regressions, study usage patterns, or compare provider telemetry following a release.
How do I add Convai Analytics to my agent?
Install @convai/analytics-mcp, add it as a stdio MCP server, set required CONVAI_API_KEY, and optionally CONVAI_ANALYTICS_BASE_URL in your MCP client environment.