Foxcite Python SDK

The official Python client library for the Foxcite API. Foxcite is an Answer Engine Optimization (AEO) and ai search visibility tool that helps modern agencies and brands track their presence across major LLMs (ChatGPT, Claude, Gemini, Grok, and Perplexity).

Features

• Fully Typed: Exposes fully typed Pydantic v2 schemas for all requests and responses.
• Sync & Async Support: Native support for both synchronous (requests) and asynchronous (httpx) execution.
• High Concurrency Ready: Built-in connection pooling and socket management designed for high-throughput AI agent loops.

Installation

pip install foxcite-sdk

Quick Start

You can generate an API Key from your Foxcite Dashboard.

Synchronous Client

from foxcite import Foxcite

# The client uses a context manager to gracefully handle connection pools
with Foxcite(api_key="seomd_live_...") as client:
    # List brand workspaces
    brands = client.brands.list()
    print("Brands:", [b.name for b in brands])

    # Execute a quick AEO audit
    audit = client.audits.quick_audit(
        name="My Brand",
        domain="mybrand.com",
        niche="SaaS Analytics",
        query="best saas analytics tools"
    )
    print("Quick Audit Scan ID:", audit.scan_id)

Asynchronous Client

import asyncio
from foxcite import AsyncFoxcite

async def main():
    async with AsyncFoxcite(api_key="seomd_live_...") as client:
        brands = await client.brands.list()
        print("Brands:", [b.name for b in brands])

if __name__ == "__main__":
    asyncio.run(main())

Developer Notes: Connection Pooling

Under the hood, the Python SDK manages persistent TCP connections.

• The synchronous Foxcite client utilizes a requests.Session().
• The asynchronous AsyncFoxcite client utilizes an httpx.AsyncClient().

Always use the client within a with or async with context manager to ensure sockets are properly released, preventing file descriptor leaks during high-concurrency background tasks.

Contributing

1. Clone the repository.
2. Create a virtual environment: python3 -m venv .venv && source .venv/bin/activate
3. Install dependencies: pip install -e .
4. Run tests: pytest tests/

Resources

• Homepage
• Bug Tracker