Skip to main content
Glama

Azure Assistant MCP

by iOSDevil
kql_loader.py1.23 kB
from __future__ import annotations import os import re from pathlib import Path from typing import Optional _FENCE_RE = re.compile(r"```\s*kql\s*\n(.*?)\n```", re.DOTALL | re.IGNORECASE) def _base_dir() -> Path: # Allow override via env var; else default next to this file in kql/ override = os.environ.get("AZURE_ASSISTANT_KQL_PATH") if override: return Path(override) return Path(__file__).resolve().parent / "kql" def load_kql_template(name: str) -> Optional[str]: """Load a KQL template by name. Supports either plain `.kql` files or Markdown with a fenced ```kql block. Returns None if no template is found or parse fails. """ base = _base_dir() # Try .kql first kql_path = base / f"{name}.kql" if kql_path.is_file(): try: return kql_path.read_text(encoding="utf-8").strip() except Exception: pass # Try .md with fenced code block md_path = base / f"{name}.md" if md_path.is_file(): try: text = md_path.read_text(encoding="utf-8") m = _FENCE_RE.search(text) if m: return m.group(1).strip() except Exception: pass return None

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/iOSDevil/Azure-Assistant-MCP'

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