Convai Analytics

io.github.Conv-AI由 GitHub 账号 Conv-AI 发布v0.2.5更新于 Oct 24, 2026

Analyze Convai sessions, latency, reliability, usage, and provider telemetry via API key.

已验证STDIO仅桌面数据与分析AI 与机器学习

概览

AI 生成的概览

让助手通过托管的 Convai Analytics API 查询 Convai 语音智能体的会话、延迟、可靠性、用量以及提供商和模型表现。

可以做什么
这是一个本地 stdio MCP 服务器,封装公开的 Convai Analytics SDK,提供账户摘要、会话列表与时间线、交互追踪、延迟分位数与组件分解、错误与可靠性趋势、用量与并发估算,以及 TTS/LLM 提供商对比等工具。许多工具返回结构化 JSON 和 Vega-Lite 图表规格,并附带提示模板,覆盖会话为何变慢、延迟趋势等常见问题。受套餐限制的工具在账户套餐不支持时会返回类型化错误。
适用场景
当你已有 Convai 语音智能体,并希望助手无需编写 SDK 脚本即可回答关于它们的运维问题——延迟、可靠性、用量、并发或提供商与模型表现——时使用。它面向客户侧分析,而不是内部基础设施访问。
运行要求
通过 stdio 在本地运行,通常用 npx 从 npm 包 @convai/analytics-mcp 启动,因此需要 Node.js 和网络访问。必须在环境变量 CONVAI_API_KEY 中提供 Convai API 密钥。可选的 CONVAI_ANALYTICS_BASE_URL 用于覆盖分析 API 基础地址,通常应保持未设置。修改配置后需重启 MCP 宿主。
安装前请注意
服务器需要密钥 CONVAI_API_KEY,不应将其写入源代码、提交到 MCP 配置、截图或日志中。它只调用公开的 Convai Analytics API,不接受账户覆盖或内部凭据,工具结果经过清理,错误不会回显该密钥。分析查询为只读,但会把账户数据发送到托管的 Convai 分析服务。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Convai Analytics,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

@convai/analytics-mcp

Local stdio MCP server for Convai Analytics.

This package is the recommended agent interface for Convai Analytics. It lets MCP-capable agents answer questions about your Convai sessions, latency, reliability, usage, and provider/model performance without writing custom SDK scripts. It wraps the public @convai/analytics TypeScript SDK, uses CONVAI_API_KEY, and returns structured JSON plus Vega-Lite chart specs.

Package: @convai/analytics-mcp

Official MCP Registry name: io.github.Conv-AI/convai-analytics-mcp

Install And Run

bash
export CONVAI_API_KEY="ck_live_your_key_here"npx -y @convai/analytics-mcp@latest

Optional:

bash
export CONVAI_ANALYTICS_BASE_URL="https://analytics-api.convai.com/v1/analytics"

Leave CONVAI_ANALYTICS_BASE_URL unset for production. Do not put the API key in source code, committed MCP config, screenshots, or logs.

After adding or changing MCP config, restart Claude Desktop, Claude Code, Cursor, Codex, or your MCP host so it reloads the server command and CONVAI_API_KEY.

Claude Desktop

json
{  "mcpServers": {    "convai-analytics": {      "command": "npx",      "args": ["-y", "@convai/analytics-mcp@latest"],      "env": {        "CONVAI_API_KEY": "ck_live_your_key_here"      }    }  }}

After saving this config, quit and reopen Claude Desktop so it starts the new MCP server.

Cursor / Codex-Compatible MCP Clients

Use the same stdio command:

json
{  "command": "npx",  "args": ["-y", "@convai/analytics-mcp@latest"],  "env": {    "CONVAI_API_KEY": "ck_live_your_key_here"  }}

For Claude Code, Cursor, Codex-compatible clients, and other stdio MCP hosts, restart the client or start a new session after adding or changing MCP config.

Security Model

The server is customer-facing and public-safe by design:

  • It only calls the public Convai Analytics API through @convai/analytics.
  • It does not accept account overrides, service credentials, database URLs, or other internal access paths.
  • Account scoping, plan gating, and quota enforcement stay server-side in the hosted analytics API.
  • Tool results are sanitized so errors do not echo CONVAI_API_KEY.

Tools

Core and account tools:

  • get_summary
  • get_metrics_catalog
  • list_sessions
  • get_session_timeline
  • get_interaction_trace

Latency tools:

  • get_p95_latency_over_time
  • get_latency_percentile_series
  • get_latency_percentile_chart
  • get_latency_threshold_chart
  • get_latency_heatmap_chart
  • get_component_latency_breakdown
  • generate_component_latency_chart
  • find_component_latency_bottlenecks
  • generate_interaction_waterfall
  • explain_slow_session

Reliability tools:

  • get_error_trend
  • generate_error_trend_chart
  • get_error_breakdown
  • generate_error_breakdown_chart
  • get_dropped_error_persist_trend
  • generate_dropped_error_persist_chart
  • generate_reliability_summary_chart
  • generate_reliability_trends_chart

These reliability tools use error and dropped-persistence metrics that are available today. If an agent asks for a status distribution, only use group_by=status when the returned rows contain real non-empty status groups; otherwise report that status-tagged aggregate telemetry is not available for that range.

Usage and concurrency tools:

  • get_usage_trends
  • generate_usage_trends_chart
  • get_character_usage_leaderboard
  • generate_character_usage_chart
  • generate_session_duration_scatter
  • estimate_active_session_concurrency
  • generate_active_session_concurrency_chart
  • generate_peak_concurrency_chart

Provider and model tools:

  • get_tts_provider_attribution
  • generate_tts_provider_chart
  • get_llm_model_latency
  • generate_llm_model_latency_chart
  • compare_providers

Plan-gated advanced tools:

  • detect_regressions
  • advanced_query

Plan-gated tools return typed MCP tool errors for 402/403 responses with the required plan in the message.

Prompts

The server exposes prompt templates for common customer questions:

  • why_was_this_session_slow
  • aggregate_latency_distribution
  • p95_latency_trend
  • component_bottlenecks
  • trace_explanation
  • error_rate_trends
  • provider_comparison
  • usage_summary

Resources

  • convai://analytics/docs/concepts
  • convai://analytics/docs/metrics-reference
  • convai://analytics/docs/authentication
  • convai://analytics/catalog

The catalog resource fetches the caller's account catalog when CONVAI_API_KEY is available.

Example Questions

text
How many interactions and unique end users did I have in the last 30 days?Break it down by character and generate a usage trend chart.
text
Show aggregate P50/P95/P99 voice.user_to_bot_latency for production readiness sign-off.Add a 3000 ms p95 threshold line and summarize the worst buckets.
text
Explain why session s_123 was slow and generate an interaction waterfall if there is a traceable interaction.
text
Show reliability trends, errors by component, and dropped error-persistence events.
text
Estimate active session concurrency and show the peak concurrency chart.

Local Development

From the repo root:

bash
make mcp-installmake mcp-lintmake mcp-testmake mcp-buildmake mcp-smoke

Live smoke against production with your own key:

bash
export CONVAI_API_KEY="ck_live_your_key_here"export CONVAI_ANALYTICS_BASE_URL="https://analytics-api.convai.com/v1/analytics"export CONVAI_ANALYTICS_E2E_RANGE="last_30d"cd packages/mcpnpm run e2e:prod

The live smoke accepts empty data for accounts without recent traffic and treats plan-gated 402/403 responses as valid gated results.

Discovery

The canonical MCP registry manifest is server.json. The server is published to npm and the Official MCP Registry. Additional directories and marketplaces such as GitHub MCP Registry, Smithery, Glama, PulseMCP, mcp.so, and Docker MCP Catalog can reference the same package and registry metadata.

来源:packages/mcp/README.md,提交 35cbf99

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.2.5最新Sep 16, 2026

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