Helicone review
A Lunary-authored review of Helicone’s AI gateway, observability, prompts, exports and MCP access.
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Helicone combines model-provider access with request observability, prompt management and datasets.
Strength
A common AI gateway with request-level observability.
Check first
Streaming, retries and application steps outside the gateway.
About this review
Based on official docs, without measured latency or price claims.
At a glance
| Check | Trial evidence |
|---|---|
| Provider compatibility | Representative requests use the intended models |
| Streaming and failure behavior | Completed output, error, and retry evidence |
| Application context | Tools and sessions reconstruct a complete task |
| Prompt workflow | Served prompt version linked to the inspected request |
| Portability | Archive includes required bodies and custom properties |
What changes in your stack
Helicone can sit between your application and model providers. Test the endpoints, models, credentials and failure behavior your application uses.
Beyond request logs
Helicone documents prompt management, datasets, exports and an observability MCP server. Tool execution outside the provider request may need additional instrumentation.
Export the data you need
ETL exports distinguish request metadata from optional bodies. Select the correct region and preserve sessions and custom properties for later analysis.
Questions & answers
Does Helicone manage prompts?
Yes. Its prompt management integrates with the AI Gateway.
Can an assistant query Helicone data?
Yes, through its documented observability MCP server; check tools and access scope.
By Lunary · Documentation reviewed Sep 16, 2026
Sources & methodology (7)
Based on vendor documentation, not an independent benchmark or hands-on rating. Features and plans can change.
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