> ## Documentation Index
> Fetch the complete documentation index at: https://docs.financialdatasets.ai/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> The Financial Datasets API is served at https://api.financialdatasets.ai. Authenticate with the `X-API-KEY` header; create keys at https://financialdatasets.ai. Agents can open and fund their own account without a dashboard: see https://docs.financialdatasets.ai/agents.md.
> Tool-using agents can call Financial Datasets without writing code through the hosted MCP server at https://mcp.financialdatasets.ai/.
> The OpenAPI spec at https://financialdatasets.ai/openapi.json is the source of truth for request and response schemas.
> The index of every docs page is at https://docs.financialdatasets.ai/llms.txt. Append .md to any docs URL to get that page as Markdown.

# Quickstart

> Make your first Search request in under 2 minutes.

Search accepts a query in natural language and returns the passages of financial documents that answer it, each with a citation that opens the source document at that passage.

<Note>
  **Alpha.** Access is by invitation. Contact us to request access.
</Note>

## 1. Get an API key

Sign up at [financialdatasets.ai](https://financialdatasets.ai) and generate your **API key** from the dashboard. Search uses the same key as every other endpoint.

## 2. Send a query

<CodeGroup>
  ```python Python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
  import requests

  response = requests.post(
      "https://api.financialdatasets.ai/search",
      headers={"X-API-KEY": "your_api_key_here"},
      json={
          "query": "committee retainers",
          "filters": {"identifiers": {"ticker": ["CCI"]}},
      },
  )

  for result in response.json()["results"]:
      print(result["title"], result["url"])
      for excerpt in result["excerpts"]:
          print(excerpt["text"], excerpt["citation"]["link"])
  ```

  ```javascript JavaScript theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
  const response = await fetch("https://api.financialdatasets.ai/search", {
    method: "POST",
    headers: { "X-API-KEY": "your_api_key_here", "Content-Type": "application/json" },
    body: JSON.stringify({
      query: "committee retainers",
      filters: { identifiers: { ticker: ["CCI"] } },
    }),
  });

  const { results } = await response.json();
  for (const result of results) {
    console.log(result.title, result.url);
    for (const excerpt of result.excerpts) {
      console.log(excerpt.text, excerpt.citation.link);
    }
  }
  ```

  ```bash cURL theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
  curl -s -X POST "https://api.financialdatasets.ai/search" \
    -H "Content-Type: application/json" \
    -H "X-API-KEY: $FINANCIAL_DATASETS_API_KEY" \
    -d '{
      "query": "committee retainers",
      "filters": { "identifiers": { "ticker": ["CCI"] } }
    }'
  ```
</CodeGroup>

## 3. Read the response

Each result is one document. Each excerpt is a passage from that document, reproduced verbatim, with a link that opens the document at the passage.

```json theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
{
  "title": "Crown Castle Inc · DEF 14A 2026",
  "url": "https://www.sec.gov/Archives/edgar/data/1051470/000105147026000039/cci-20260406.htm",
  "date": "2026-04-06",
  "excerpts": [
    {
      "text": "2025 Committee Retainers(a)\nBoard Committee | Committee Chair | Committee Member(b)\nAudit Committee | $30,000 | $15,000\nCEO Search Committee | $20,000 | $10,000\nCHC Committee | $25,000 | $12,500\nFiber Review Committee | $25,000 | $12,500 ...",
      "citation": {
        "document": "0001051470-26-000039",
        "date": "2026-04-06",
        "section": "Crown Castle Inc. > 2025 Committee Retainers(a)",
        "link": "https://www.sec.gov/Archives/edgar/data/1051470/000105147026000039/cci-20260406.htm#:~:text=Committee%20Member%28b%29,N%26G%20Committee"
      },
      "attributes": { "kind": "table" }
    }
  ]
}
```

## Next steps

<CardGroup cols={2}>
  <Card title="Introduction" icon="book-open" href="/search/introduction">
    Writing queries, filters, the full response shape, and errors.
  </Card>

  <Card title="Best Practices" icon="lightbulb" href="/search/best-practices">
    Improve precision: the query form, filters, and diagnosis.
  </Card>
</CardGroup>


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