Skip to main content
Glama

mcp-run-python

Official
by pydantic
google_gla.py1.95 kB
from __future__ import annotations as _annotations import os import httpx from typing_extensions import deprecated from pydantic_ai import ModelProfile from pydantic_ai.exceptions import UserError from pydantic_ai.models import cached_async_http_client from pydantic_ai.profiles.google import google_model_profile from pydantic_ai.providers import Provider @deprecated('`GoogleGLAProvider` is deprecated, use `GoogleProvider` with `GoogleModel` instead.') class GoogleGLAProvider(Provider[httpx.AsyncClient]): """Provider for Google Generative Language AI API.""" @property def name(self): return 'google-gla' @property def base_url(self) -> str: return 'https://generativelanguage.googleapis.com/v1beta/models/' @property def client(self) -> httpx.AsyncClient: return self._client def model_profile(self, model_name: str) -> ModelProfile | None: return google_model_profile(model_name) def __init__(self, api_key: str | None = None, http_client: httpx.AsyncClient | None = None) -> None: """Create a new Google GLA provider. Args: api_key: The API key to use for authentication, if not provided, the `GEMINI_API_KEY` environment variable will be used if available. http_client: An existing `httpx.AsyncClient` to use for making HTTP requests. """ api_key = api_key or os.getenv('GEMINI_API_KEY') if not api_key: raise UserError( 'Set the `GEMINI_API_KEY` environment variable or pass it via `GoogleGLAProvider(api_key=...)`' 'to use the Google GLA provider.' ) self._client = http_client or cached_async_http_client(provider='google-gla') self._client.base_url = self.base_url # https://cloud.google.com/docs/authentication/api-keys-use#using-with-rest self._client.headers['X-Goog-Api-Key'] = api_key

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pydantic/pydantic-ai'

If you have feedback or need assistance with the MCP directory API, please join our Discord server