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Teradata MCP Server

dba_userSqlList

Retrieve SQL queries executed by specific users or all users within a defined timeframe to monitor database activity and audit query history.

Instructions

Get a list of SQL run by a user in the last number of days if a user name is provided, otherwise get list of all SQL in the last number of days.

Arguments: user_name - user name no_days - number of days

Returns: ResponseType: formatted response with query results + metadata

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_nameYes
no_daysNo

Implementation Reference

  • Handler function executing the dba_userSqlList tool: retrieves SQL queries run by a specific user (or all if none specified) in the last N days from Teradata's DBC.QryLog views.
    def handle_dba_userSqlList(conn: TeradataConnection, user_name: str, no_days: int | None = 7,  *args, **kwargs):
        """
        Get a list of SQL run by a user in the last number of days if a user name is provided, otherwise get list of all SQL in the last number of days.
    
        Arguments:
          user_name - user name
          no_days - number of days
    
        Returns:
          ResponseType: formatted response with query results + metadata
        """
        logger.debug(f"Tool: handle_dba_userSqlList: Args: user_name: {user_name}")
    
        with conn.cursor() as cur:
            if user_name == "":
                logger.debug("No user name provided, returning all SQL queries.")
                rows = cur.execute(f"""SELECT t1.QueryID, t1.ProcID, t1.CollectTimeStamp, t1.SqlTextInfo, t2.UserName
                FROM DBC.QryLogSqlV t1
                JOIN DBC.QryLogV t2
                ON t1.QueryID = t2.QueryID
                WHERE t1.CollectTimeStamp >= CURRENT_TIMESTAMP - INTERVAL '{no_days}' DAY
                ORDER BY t1.CollectTimeStamp DESC;""")
            else:
                logger.debug(f"User name provided: {user_name}, returning SQL queries for this user.")
                rows = cur.execute(f"""SELECT t1.QueryID, t1.ProcID, t1.CollectTimeStamp, t1.SqlTextInfo, t2.UserName
                FROM DBC.QryLogSqlV t1
                JOIN DBC.QryLogV t2
                ON t1.QueryID = t2.QueryID
                WHERE t1.CollectTimeStamp >= CURRENT_TIMESTAMP - INTERVAL '{no_days}' DAY
                AND t2.UserName = '{user_name}'
                ORDER BY t1.CollectTimeStamp DESC;""")
            data = rows_to_json(cur.description, rows.fetchall())
            metadata = {
                "tool_name": "dba_userSqlList",
                "user_name": user_name,
                "no_days": no_days,
                "total_queries": len(data)
            }
            logger.debug(f"Tool: handle_dba_userSqlList: metadata: {metadata}")
            return create_response(data, metadata)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries the full burden. It explains the output is a formatted response with query results and metadata, but lacks disclosure of side effects, permissions, rate limits, or data freshness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, using a single sentence for the main behavior and a structured list for arguments/returns with no superfluous content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description does not detail return format beyond 'formatted response'. Missing information on sorting, limits, pagination, or maximum days. Adequate for a simple list but leaves gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, meaning the description does not add meaning beyond parameter names and types. The description lists arguments with minimal explanations ('user_name - user name') and does not provide examples, constraints, or formatting details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it gets a list of SQL run by a user or all SQL in the last number of days, with conditional logic based on whether a user name is provided. This is specific and distinguishes it from siblings like base_readQuery or dba_tableSqlList.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives like dba_tableSqlList or base_readQuery. The conditional logic provides some context but no when-not-to-use instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.