MIAPI is a developer API that delivers web-grounded AI answers with inline citations and source links, compatible with the OpenAI API format.
Each check below is a fact we could verify from public sources. Unknown checks are excluded from the calculation instead of counting as a negative, and the score is pulled toward the midpoint when coverage is low — that is what data coverage reports.
Not determined: Webhooks / automation hooks, Open-source core, Self-hosting possible.
Not determined: Business / enterprise tier, Team collaboration, Admin / role management, SSO available, Security / compliance information, Customer data export, Documented support channels.
Not determined: Free tier, Free trial, No card required to start, Cancellation / refund policy, Browser app, Mobile app, Desktop app.
Not determined: Privacy policy, Terms of service, Official documentation, Identifiable vendor, Changelog / release notes, Status page.
Scores are calculated by AimostAll with fixed, public rules (methodology v1). AI assists only with factual research; it never picks the number. Placement and scores cannot be bought.
If you're building an AI feature that needs to be factually accurate, MIAPI solves the problem most LLM APIs don't: it grounds every answer in real-time web search results and attaches inline citations so you know exactly where the information came from.
The core product is a single API call that returns a web-grounded answer, source URLs, citation markers, and a confidence score. It's built as an OpenAI-compatible drop-in — swap the base URL and it slots directly into anything already calling /v1/chat/completions, including LangChain pipelines and Cursor integrations. For developers who've spent time wrestling with hallucinations in production, that's a meaningful shortcut.
**Response accuracy** is the main differentiator. Rather than relying on a model's training data, each query runs a live web search, retrieves sources, and uses them to construct the answer. The inline citation format [1][2] links directly to source material, which matters for any use case where users need to verify or trace information.
Beyond standard Q&A, there are dedicated endpoints for news search and image search, a raw search-only mode for teams building their own RAG pipelines, and a knowledge mode that lets you mix custom documents with web results. Streaming via Server-Sent Events is supported, and there's a Python SDK with both sync and async support. An MCP server integration means it can be wired into Cursor, Claude Desktop, and Windsurf directly.
The pricing model is pay-per-query with no subscriptions. Credits don't expire, and a free tier covers 500 queries per month. Paid tiers start from a low base rate per 1,000 queries, scaling to enterprise custom pricing. For low-volume projects or prototyping, the free tier is genuinely usable.
MIAPI is a solo-developer product that launched recently on Hacker News. It's early-stage, and the lack of a dedicated pricing page or third-party reviews reflects that. For developers who need a quick, reliable way to add cited, real-time answers to an existing OpenAI-based stack, it's worth testing.
4706
2026-09-04
Medium confidence based on currently stored pricing metadata.
MIAPI is listed as a Automation tool on AimostAll.
License model: Freemium. Pricing label: Freemium.
Use this page to compare MIAPI with other automation tools, watch tutorials, and explore similar alternatives.
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MIAPI is a developer API that delivers web-grounded AI answers with inline citations and source links, compatible with the OpenAI API format.
MIAPI is listed on AimostAll as freemium with a pricing label of Freemium.
Use the alternatives section below or browse the wider automation category to compare similar tools.