About Convai Analytics
Convai Analytics is a local stdio MCP server for Convai Analytics users. It lets agents analyze sessions, latency, reliability, usage, and provider performance without custom SDK scripts, returning structured JSON and Vega-Lite chart specifications.
Key features
- 01Summarize sessions and analytics metrics
- 02Inspect session timelines and interaction traces
- 03Analyze latency and generate charts
- 04Review error trends and reliability
- 05Analyze usage, concurrency, and character metrics
- 06Compare TTS providers and LLM latency
Use cases
- 01Investigate why an individual session was slow
- 02Track latency and error trends
- 03Analyze character usage and active-session concurrency
- 04Compare voice providers or LLM model performance
MCP support
The local stdio MCP server uses CONVAI_API_KEY to call the Convai Analytics API and exposes tools, prompts, and resources to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y @convai/analytics-mcpCONVAI_API_KEYSecretConvai API key for the account to query.CONVAI_ANALYTICS_BASE_URLOptional analytics API base URL override.Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
44Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| range | enum | No | Relative time range.last_15m | last_1h | last_6h | last_24h | last_7d | last_30d |
| appKey | string | No | Optional Convai app key filter. |
| characterId | string | No | Optional character filter. |
| experienceId | string | No | Optional experience filter. |
Details
From the project 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
export CONVAI_API_KEY="ck_live_your_key_here"
npx -y @convai/analytics-mcp@latest
Optional:
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
{
"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:
{
"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_summaryget_metrics_cataloglist_sessionsget_session_timelineget_interaction_trace
Latency tools:
get_p95_latency_over_timeget_latency_percentile_seriesget_latency_percentile_chartget_latency_threshold_chartget_latency_heatmap_chartget_component_latency_breakdowngenerate_component_latency_chartfind_component_latency_bottlenecksgenerate_interaction_waterfallexplain_slow_session
Reliability tools:
get_error_trendgenerate_error_trend_chartget_error_breakdowngenerate_error_breakdown_chartget_dropped_error_persist_trendgenerate_dropped_error_persist_chartgenerate_reliability_summary_chartgenerate_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_trendsgenerate_usage_trends_chartget_character_usage_leaderboardgenerate_character_usage_chartgenerate_session_duration_scatterestimate_active_session_concurrencygenerate_active_session_concurrency_chartgenerate_peak_concurrency_chart
Provider and model tools:
get_tts_provider_attributiongenerate_tts_provider_chartget_llm_model_latencygenerate_llm_model_latency_chartcompare_providers
Plan-gated advanced tools:
detect_regressionsadvanced_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_slowaggregate_latency_distributionp95_latency_trendcomponent_bottleneckstrace_explanationerror_rate_trendsprovider_comparisonusage_summary
Resources
convai://analytics/docs/conceptsconvai://analytics/docs/metrics-referenceconvai://analytics/docs/authenticationconvai://analytics/catalog
The catalog resource fetches the caller's account catalog when CONVAI_API_KEY is available.
Example Questions
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.
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.
Explain why session s_123 was slow and generate an interaction waterfall if there is a traceable interaction.
Show reliability trends, errors by component, and dropped error-persistence events.
Estimate active session concurrency and show the peak concurrency chart.
Local Development
From the repo root:
make mcp-install
make mcp-lint
make mcp-test
make mcp-build
make mcp-smoke
Live smoke against production with your own key:
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/mcp
npm 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.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.