Span schema mapper
GenAI Span Mapper turns GenAI span mapping MCP work into span schema mapper that can be reviewed, exported, and reused by the next stakeholder.
Remote MCP for AI observability schemas
Normalize GenAI spans before dashboards tell competing stories.
A remote MCP schema mapper for OpenTelemetry GenAI spans, provider attributes, missing fields, dashboard schemas, and mapping receipts.
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What it delivers
The workflow is built around the buying intent behind GenAI span mapping MCP: fast proof, clean handoff, and a durable record.
GenAI Span Mapper turns GenAI span mapping MCP work into span schema mapper that can be reviewed, exported, and reused by the next stakeholder.
GenAI Span Mapper turns GenAI span mapping MCP work into provider rules that can be reviewed, exported, and reused by the next stakeholder.
GenAI Span Mapper turns GenAI span mapping MCP work into missing attribute detection that can be reviewed, exported, and reused by the next stakeholder.
GenAI Span Mapper turns GenAI span mapping MCP work into normalized json that can be reviewed, exported, and reused by the next stakeholder.
GenAI Span Mapper turns GenAI span mapping MCP work into dashboard schema export that can be reviewed, exported, and reused by the next stakeholder.
GenAI Span Mapper turns GenAI span mapping MCP work into mapping receipts that can be reviewed, exported, and reused by the next stakeholder.
Workflow
Submit span samples, provider names, and field dictionaries.
Map fields into OpenTelemetry GenAI attributes and dashboard schemas.
Flag missing attributes and provider-version drift.
Return normalized JSON and archive a mapping receipt.
Pricing
Prices are shown as monthly rates. Annual checkout applies a 50% annual discount in hosted payment.
One service and 2,000 span maps
Team observability schemas
Multi-service telemetry governance
Resources
How to evaluate GenAI span mapping MCP with practical steps, risks, and a product workflow.
How to evaluate OpenTelemetry GenAI attributes MCP with practical steps, risks, and a product workflow.
How to evaluate LLM observability schema gate with practical steps, risks, and a product workflow.
How to evaluate AI telemetry mapping receipt with practical steps, risks, and a product workflow.
How to evaluate GenAI span JSON normalizer with practical steps, risks, and a product workflow.
How to evaluate remote MCP observability tool with practical steps, risks, and a product workflow.
How to evaluate LLM span diff MCP with practical steps, risks, and a product workflow.
How to evaluate AI observability schema mapper with practical steps, risks, and a product workflow.