Skip to main content
Glama
by chatmcp
extract.py823 B
import os import logging from openai import OpenAI from mcp_server_collector.prompts import extract_mcp_servers_prompt logger = logging.getLogger("mcp-server-collector") async def extract_mcp_servers_from_content(content: str) -> str | None: client = OpenAI( api_key=os.getenv("OPENAI_API_KEY"), base_url=os.getenv("OPENAI_BASE_URL"), ) user_content = extract_mcp_servers_prompt.format(content=content) logger.info(f"Extract prompt: {user_content}") chat_completion = client.chat.completions.create( messages=[ { "role": "user", "content": user_content, } ], model=os.getenv("OPENAI_MODEL"), response_format={"type": "json_object"}, ) return chat_completion.choices[0].message.content

Latest Blog Posts

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/chatmcp/mcp-server-collector'

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