Skip to main content
Glama
nebula-contrib

NebulaGraph MCP Server

execute_query

Run queries on NebulaGraph database to retrieve graph data and insights from specified spaces.

Instructions

Execute a query Args: query: The query to execute space: The space to use Returns: The results of the query

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
spaceYes

Implementation Reference

  • The 'execute_query' tool handler function. Decorated with @mcp.tool(), it connects to NebulaGraph, switches to the specified space, executes the provided query, formats and returns the results or error message.
    @mcp.tool()
    def execute_query(query: str, space: str) -> str:
        """Execute a query
        Args:
            query: The query to execute
            space: The space to use
        Returns:
            The results of the query
        """
        pool = get_connection_pool()
        session = pool.get_session(
            os.getenv("NEBULA_USER", "root"), os.getenv("NEBULA_PASSWORD", "nebula")
        )
    
        try:
            session.execute(f"USE {space}")
            result = session.execute(query)
            if result.is_succeeded():
                # Format the query results
                if result.row_size() > 0:
                    columns = result.keys()
                    output = "Results:\n"
                    output += " | ".join(columns) + "\n"
                    output += "-" * (len(" | ".join(columns))) + "\n"
    
                    # Iterate through all rows
                    for i in range(result.row_size()):
                        row = result.row_values(i)
                        output += " | ".join(str(val) for val in row) + "\n"
                    return output
                return "Query executed successfully (no results)"
            else:
                return f"Query failed: {result.error_msg()}"
        finally:
            session.release()
  • The @mcp.tool() decorator registers the 'execute_query' function as an MCP tool.
    @mcp.tool()
  • Function signature and docstring define the input schema (query: str, space: str) and output (str) for the tool, used by MCP for validation.
    def execute_query(query: str, space: str) -> str:
        """Execute a query
        Args:
            query: The query to execute
            space: The space to use
        Returns:
            The results of the query
        """

Tool Definition Quality

Score is being calculated. Check back soon.

Install Server

Other Tools

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/nebula-contrib/nebulagraph-mcp-server'

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