A developer-focused API that returns AI-generated answers grounded in real-time web research, complete with source citations. Supports Python, JavaScript, and cURL with streamed responses via server-sent events.
Try MIAPI
MIAPI is built for developers who need web-grounded AI answers without standing up their own search and retrieval infrastructure. If you are building a research assistant, a customer support bot, or augmenting a RAG pipeline with live web data, this is a genuinely low-friction starting point at a price that is hard to argue with. The free tier lets you validate the concept before committing, and the Pro plan at $10/month is cheap enough to prototype seriously. The main question is whether the depth of web grounding and answer quality hold up under production workloads, and whether the sparse documentation and limited integrations will slow you down.
Note: The headline says "$9/month" but the actual Pro tier is listed at $10/month on their site. Plan accordingly.
Good for testing the API and validating your use case before committing.
The sweet spot for indie developers and small teams shipping production features.
For teams that need SLAs, higher rate limits, or custom configurations.
One thing worth noting: the pricing page is vague about rate limits and request caps on each tier. "Basic features" and "Limited access" on the Free plan do not tell you how many queries you actually get. Ask before you build around it.
Answers are generated from live web research, not a static knowledge cutoff. This is the core value proposition. Every response pulls from current web sources and includes citations so you can verify claims.
Every answer comes with URLs pointing to the sources used. This is critical for building trust in user-facing applications and for debugging answer quality in your pipeline.
Responses stream via SSE, which means your UI can render tokens as they arrive. This is table stakes for modern AI integrations, and MIAPI handles it natively rather than forcing you to poll.
Works with Python, JavaScript, and cURL out of the box. No proprietary SDK required. If you can make an HTTP request, you can use MIAPI.
The SSE streaming approach means time-to-first-token is optimized. For chat interfaces and interactive tools, this matters more than total response time.
Designed to slot into retrieval-augmented generation workflows. Use MIAPI as the web retrieval layer and combine it with your own vector store or domain-specific data.
If you are building a tool that needs to answer questions with current, cited information, MIAPI handles the hard part: searching the web, synthesizing results, and returning structured answers with sources. You focus on the UX.
Bots that need to reference current documentation, pricing pages, or policy updates benefit from web-grounded answers. MIAPI can supplement your knowledge base with live web lookups when internal docs fall short.
Running your own search infrastructure (Serper, SerpAPI, Bing API, plus an LLM, plus a citation pipeline) is expensive and complex. MIAPI bundles all of that into a single API call at $10/month. That is a meaningful shortcut.
If your retrieval-augmented generation system needs a web search fallback for queries outside your vector store, MIAPI can serve as that layer. Plug it in as a secondary retriever when your internal corpus has no relevant hits.
Start with the free tier to test answer quality and latency. If it fits your workflow, $10/month is a low bar for production use.