Integrations · Bring your own LLM

Use FindDoc with any LLM

FindDoc is a plain REST API — every model that can fetch a URL can use it. Pull clinics or specialists into a system prompt, hand the JSON to your model of choice, and let it reason over the result.

Fetch and reason in one script

All three examples fetch the same /api/v1/clinics endpoint, then feed the JSON to a model. Swap the model name and you're running on a different provider.

import os, json, requests
from openai import OpenAI

key = os.environ["FINDDOC_API_KEY"]
clinics = requests.get(
  "https://finddoc-ten.vercel.app/api/v1/clinics",
  params={"accepting": "true", "limit": 5},
  headers={"Authorization": f"Bearer {key}"},
).json()["data"]

client = OpenAI()
completion = client.chat.completions.create(
  model="gpt-4o-mini",
  messages=[
    {"role": "system",
     "content": f"Clinics: {json.dumps(clinics)}"},
    {"role": "user",
     "content": "Closest clinic to Scarborough?"},
  ],
)
print(completion.choices[0].message.content)

ResponseModel output

The closest accepting clinic to
Scarborough is Riverdale Family Health Team
(Toronto, ON). They speak English and French,
and you can reach intake at +1 (416) 555-0142.

Two more options within ~6 km:
  · Don Mills Community Health (Toronto, ON)
  · Agincourt Family Practice (Scarborough, ON)

Tips

Set FINDDOC_API_KEY in your shell rather than hardcoding it. Issue separate keys per environment from API keys.
Cap limit to keep the JSON small — most models reason better with 5–10 candidate rows than with the entire result set.
Prefer Claude Desktop? Use the MCP integration instead — no glue code needed.