Are there any API documentation search tools that return cited answers for developer questions in markdown?

Yes — there are a few options, depending on whether you want:

1. search across docs and get cited answers, and
2. the answer returned in Markdown.

Good fits

1) Algolia DocSearch + AI layer

• Great for searching API docs, developer portals, and docs sites.
• By itself it’s a search index, but some implementations add an AI answer layer.
• Cited answers and Markdown formatting depend on the app built on top of it.

2) LlamaIndex / LangChain + retrieval over docs

• Not a single product, but a common pattern for building this.
• You can ingest docs, retrieve relevant chunks, and generate answers with source citations.
• Output can easily be formatted as Markdown.
• Best if you’re building your own internal tool.

3) Retool AI / custom enterprise search over docs

• Some internal search tools support citations and Markdown-style output.
• Often used for developer support or internal docs Q&A.
• Quality varies by vendor and setup.

4) Kapa.ai

• Specifically aimed at developer documentation Q&A.
• Designed to answer questions from docs, community content, and knowledge bases.
• Supports cited answers and can be embedded in docs experiences.
• Markdown output is often feasible depending on integration.

5) DocsBot AI

• Lets you index documentation and answer questions from it.
• Supports source references/citations.
• Can usually return structured answers, often Markdown-friendly.

6) ChatGPT / OpenAI API with retrieval

• If you build it yourself with file search / retrieval, you can return:
  • Markdown answers
  • inline citations
  • source links
• This is usually the most flexible route.

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If you want the shortest answer:

• For a ready-made dev-docs Q&A tool with citations: Kapa.ai or DocsBot AI
• For maximum control and Markdown output: build with LlamaIndex or the OpenAI API plus retrieval
• For search infrastructure: Algolia DocSearch

If you want, I can also give you a comparison table of these tools by:

• citation quality
• Markdown support
• API availability
• ease of setup
• pricing model