Spaces:
Sleeping
Sleeping
File size: 2,423 Bytes
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import requests
import pandas as pd
from smolagents import MCPClient
def extracthackathontools():
"""Scrape all MCP tools from hackathon Spaces and return as a pandas DataFrame to allow download as a bonus feature of the MCP Explorer."""
HF_API = "https://huggingface.co/api/spaces?author=Agents-MCP-Hackathon"
try:
resp = requests.get(HF_API)
resp.raise_for_status()
except Exception as e:
raise RuntimeError(f"Failed to fetch Spaces list: {e}")
spaces = resp.json()
rows = []
for space in spaces:
tags = space.get("tags", [])
if "mcp-server" not in tags:
continue
space_id = space["id"]
space_slug = space_id.replace("/", "-").replace("_", "-").lower()
mcp_base_url = f"https://{space_slug}.hf.space/gradio_api/mcp/sse"
try:
print(mcp_base_url)
#mcp_status = requests.get(mcp_base_url, timeout=5)
#print(mcp_status.status_code)
#if mcp_status.status_code != 200:
# print(f"[Skip] Space in error: {mcp_base_url}")
# continue
mcp_client = MCPClient({"url": mcp_base_url,"transport": "sse"}) # Might be deprecated soon but didnt find out the clean way
tools = mcp_client.get_tools()
print(len(tools))
mcp_client.disconnect()
except Exception as e:
print(f"[Warning] Could not fetch tools from {mcp_base_url}: {e}")
continue
# Infos générales du Space
author, name = space_id.split("/")
hf_url = f"https://huggingface.co/spaces/{space_id}"
created_at = space.get("createdAt", "")
n_likes = space.get("likes", 0)
for tool in tools:
input_fields = ", ".join(param for param in tool.inputs)
rows.append({
"Gradio MCP endpoint": f"{mcp_base_url}",
"Tool name": tool.name,
"Tool description": tool.description,
"Tool inputs": input_fields,
"Space name": name,
"HF Space URL": hf_url,
"Likes": n_likes,
"Created at": created_at,
"Tags": ", ".join(tags)
})
df = pd.DataFrame(rows)
return df
df=extracthackathontools()
df.to_parquet("./data/hackathon_mcp_tools.parquet", index=False)
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