Prompt
What should I use for API docs with analytics?
Latest observation
If you want API docs plus analytics, the best choice depends on whether you want a hosted product or a self-hosted/open-source setup.
Best hosted options
- ReadMe — very popular for API docs with built-in analytics, search, feedback, and a polished docs experience.
- Stoplight — good if you want OpenAPI-first docs, design/testing, and some analytics/insights.
- Postman — useful if your team already uses Postman; docs and usage insights are decent, but it’s less “docs-first” than ReadMe.
Best open-source / self-hosted direction
- Docusaurus or MkDocs + Plausible/Google Analytics/PostHog
- More flexible and cheaper.
- You assemble docs + analytics yourself.
- Good if you want full control and don’t need turnkey API-specific analytics.
If you specifically want API usage analytics
Docs platforms often track:
- page views
- popular endpoints
- search terms
- engagement/drop-off
But if you want actual API traffic analytics like:
- request volume by endpoint
- latency
- errors
- client/version usage
you’ll usually want a separate layer like:
- PostHog
- Datadog
- Grafana/Prometheus
- Cloud provider API gateway analytics (AWS API Gateway, Azure API Management, Kong, etc.)
Quick recommendation
- Fastest “just works” choice: ReadMe
- OpenAPI + docs workflow: Stoplight
- Custom + self-hosted: Docusaurus/MkDocs + PostHog
- Need actual API usage metrics: pair docs with an API gateway/observability tool
If you want, I can recommend the best option based on your stack: OpenAPI/Swagger, REST or GraphQL, hosted vs self-hosted, and budget.
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
Want this interpreted for your brand?
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