Datasets:

evalstate
/

mcp-clients

@@ -1,167 +0,0 @@
-#!/usr/bin/env -S uv run
-# /// script
-# requires-python = ">=3.10"
-# dependencies = [
-#     "datasets",
-#     "huggingface_hub",
-# ]
-# ///
-"""
-Scheduled job to extract and update MCP clients dataset.
-This script runs via HF Jobs to keep the dataset fresh.
-Usage:
-    uv run mcp_clients_job.py [--limit N]
-"""
-import sys
-import json
-import argparse
-from datetime import datetime
-from datasets import Dataset, Features, Value
-def normalize_capabilities(caps):
-    """Normalize capabilities for comparison."""
-    if caps is None:
-        return None
-    if isinstance(caps, str):
-        if caps == '{}':
-            return {}
-        try:
-            return json.loads(caps)
-        except Exception:
-            return caps
-    return caps
-def create_dataset_from_clients(clients_list):
-    """Create a Hugging Face Dataset from the clients list."""
-    features = Features({
-        'name': Value('string'),
-        'version': Value('string'),
-        'capabilities': Value('string'),  # Store as JSON string for consistency
-        'last_seen': Value('string'),
-    })
-    records = []
-    for client in clients_list:
-        # Convert capabilities to JSON string for consistency
-        caps = client['capabilities']
-        if isinstance(caps, dict):
-            caps = json.dumps(caps, sort_keys=True)
-        elif caps is None:
-            caps = ''
-        else:
-            caps = str(caps)
-        records.append({
-            'name': client['name'],
-            'version': client['version'],
-            'capabilities': caps,
-            'last_seen': client['last_seen'],
-        })
-    return Dataset.from_list(records, features=features)
-def main():
-    parser = argparse.ArgumentParser(description="Extract and update MCP clients dataset")
-    parser.add_argument("--limit", type=int, default=None, help="Limit processing to N rows (for testing)")
-    parser.add_argument("--repo-id", default="evalstate/mcp-clients", help="Target repository ID")
-    args = parser.parse_args()
-    print(f"[{datetime.now().isoformat()}] Starting MCP clients extraction...", file=sys.stderr)
-    if args.limit:
-        print(f"[{datetime.now().isoformat()}] LIMIT MODE: Will process at most {args.limit:,} rows", file=sys.stderr)
-    unique_clients = {}
-    from datasets import load_dataset
-    ds = load_dataset('evalstate/hf-mcp-logs', 'sessions', streaming=True)
-    sessions_ds = ds['sessions']
-    total_rows = 0
-    skipped_deletes = 0
-    skipped_other = 0
-    start_time = datetime.now()
-    for batch in sessions_ds.iter(batch_size=1000):
-        batch_len = len(batch['name'])
-        total_rows += batch_len
-        # Progress indicator every 100k rows
-        if total_rows % 100000 == 0:
-            elapsed = (datetime.now() - start_time).total_seconds()
-            rate = total_rows / elapsed if elapsed > 0 else 0
-            print(f"[{datetime.now().isoformat()}] Progress: {total_rows:,} rows processed "
-                  f"({rate:.0f} rows/sec), {len(unique_clients):,} unique clients found", file=sys.stderr)
-        if args.limit and total_rows >= args.limit:
-            print(f"[{datetime.now().isoformat()}] Reached limit of {args.limit:,} rows", file=sys.stderr)
-            break
-        for i in range(batch_len):
-            method_name = batch['methodName'][i] if 'methodName' in batch else None
-            if method_name == 'session_delete':
-                skipped_deletes += 1
-                continue
-            if method_name != 'initialize':
-                skipped_other += 1
-                continue
-            name = batch['name'][i]
-            version = batch['version'][i]
-            capabilities = normalize_capabilities(batch['capabilities'][i])
-            time_str = batch['time'][i]
-            if not all([name, version, time_str]):
-                continue
-            if isinstance(capabilities, dict):
-                cap_key = json.dumps(capabilities, sort_keys=True)
-            else:
-                cap_key = str(capabilities) if capabilities is not None else None
-            key = (name, version, cap_key)
-            if key not in unique_clients or time_str > unique_clients[key]['last_seen']:
-                unique_clients[key] = {
-                    'name': name,
-                    'version': version,
-                    'capabilities': capabilities,
-                    'last_seen': time_str
-                }
-    elapsed = (datetime.now() - start_time).total_seconds()
-    rate = total_rows / elapsed if elapsed > 0 else 0
-    print(f"[{datetime.now().isoformat()}] Processing complete: {total_rows:,} rows", file=sys.stderr)
-    print(f"Rate: {rate:.0f} rows/sec, elapsed: {elapsed:.1f} seconds", file=sys.stderr)
-    print(f"Skipped {skipped_deletes:,} deletes, {skipped_other:,} non-initialize events", file=sys.stderr)
-    print(f"Found {len(unique_clients):,} unique client configurations", file=sys.stderr)
-    # Sort by last_seen descending
-    sorted_clients = sorted(
-        unique_clients.values(),
-        key=lambda x: x['last_seen'],
-        reverse=True
-    )
-    # Push to Hub
-    print(f"[{datetime.now().isoformat()}] Pushing to Hugging Face Hub...", file=sys.stderr)
-    dataset = create_dataset_from_clients(sorted_clients)
-    dataset.push_to_hub(
-        repo_id=args.repo_id,
-        commit_message=f"Update MCP clients dataset ({datetime.now().strftime('%Y-%m-%d %H:%M')})",
-    )
-    print(f"[{datetime.now().isoformat()}] Successfully pushed {len(sorted_clients):,} clients to {args.repo_id}", file=sys.stderr)
-if __name__ == '__main__':
-    main()