iflow-mcp_cryo-mcp

# Cryo MCP 🧊 A Model Completion Protocol (MCP) server for the [Cryo](https://github.com/paradigmxyz/cryo) blockchain data extraction tool. Cryo MCP allows you to access Cryo's powerful blockchain data extraction capabilities via an API server that implements the MCP protocol, making it easy to query blockchain data from any MCP-compatible client. ## For LLM Users: SQL Query Workflow Guide When using this MCP server to run SQL queries on blockchain data, follow this workflow: 1. **Download data** with `query_dataset`: ```python result = query_dataset( dataset="blocks", # or "transactions", "logs", etc. blocks="15000000:15001000", # or use blocks_from_latest=100 output_format="parquet" # important: use parquet for SQL ) files = result.get("files", []) # Get the returned file paths ``` 2. **Explore schema** with `get_sql_table_schema`: ```python # Check what columns are available in the file schema = get_sql_table_schema(files[0]) # Now you can see all columns, data types, and sample data ``` 3. **Run SQL** with `query_sql`: ```python # Option 1: Simple table reference (DuckDB will match the table name to file) sql_result = query_sql( query="SELECT block_number, timestamp, gas_used FROM blocks", files=files # Pass the files from step 1 ) # Option 2: Using read_parquet() with explicit file path sql_result = query_sql( query=f"SELECT block_number, timestamp, gas_used FROM read_parquet('{files[0]}')", files=files # Pass the files from step 1 ) ``` Alternatively, use the combined approach with `query_blockchain_sql`: ```python # Option 1: Simple table reference result = query_blockchain_sql( sql_query="SELECT * FROM blocks", dataset="blocks", blocks_from_latest=100 ) # Option 2: Using read_parquet() result = query_blockchain_sql( sql_query="SELECT * FROM read_parquet('/path/to/file.parquet')", # Path doesn't matter dataset="block…