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Abeautifulsnow

TDengine Query MCP Server

by Abeautifulsnow
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

get_field_infos

Retrieve field information for a specified stable in TDengine databases to understand data structure and schema details for query planning.

Instructions

Get the field information of the specified stable.

    Args:
        db_name (Optional[str]): The name of the database. Defaults to None. When the value is None, it means the configured database is used.
        stable_name (str): The name of the stable.

    Returns:
        TaosSqlResponse: The field information of the specified stable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
db_nameNoThe name of the database. Default is None which means the configured database.
stable_nameYesThe name of the stable

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
headYes
rowsYes
statusYes
column_metaYes

Implementation Reference

  • src/tdengine_mcp_server/server.py:261-286 (handler)
    The get_field_infos tool handler, which describes a stable in TDengine.
    @mcp.tool(name="get_field_infos")
def get_field_infos(
    ctx: Context,
    db_name: Optional[str] = Field(
        None,
        description="The name of the database. Default is None which means the configured database.",
    ),
    stable_name: str = Field(description="The name of the stable"),
) -> TaosSqlResponse:
    """Get the field information of the specified stable.

    Args:
        db_name (Optional[str]): The name of the database. Defaults to None. When the value is None, it means the configured database is used.
        stable_name (str): The name of the stable.

    Returns:
        TaosSqlResponse: The field information of the specified stable.
    """

    taos = ctx.request_context.lifespan_context.client
    if db_name is None or db_name == "":
        db_name = taos.database

    result = taos.execute_sql(f"DESCRIBE {db_name}.{stable_name};")

    return result

Tool Definition Quality

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return type (TaosSqlResponse) but fails to disclose whether the operation is read-only, what happens if the stable does not exist (error behavior), or whether rate limits apply. The Returns section merely restates the output without behavioral context.

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

Conciseness3/5

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

The docstring format with Args/Returns sections is structured but unnecessarily verbose given the schema already provides this information. The first sentence earns its place, but the Args section repeats schema content verbatim rather than adding value, and the Returns section provides minimal information beyond the type name.

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?

Given the tool has an existing output schema (per context signals) and 100% input schema coverage, the description meets minimum viability by identifying the tool's purpose. However, it lacks operational completeness (error handling, side effects) expected for a tool with no annotations to supply that context.

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

Parameters3/5

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

Schema description coverage is 100%, establishing a baseline of 3. The description largely duplicates the schema (e.g., 'The name of the stable' and the db_name default behavior) without adding significant semantic context such as valid naming patterns, case sensitivity, or examples that would help the agent formulate correct inputs.

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

Purpose4/5

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

The description opens with 'Get the field information of the specified stable,' providing a specific verb and resource. It clearly distinguishes from siblings like get_all_stables (which lists stables) and query_taos_db_data (which queries row data), though it could explicitly clarify this retrieves schema metadata rather than data.

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 guidance is provided on when to use this tool versus alternatives, prerequisites (e.g., whether the stable must exist), or workflow hints (e.g., 'use get_all_stables first to discover valid stable_name values'). The description only explains what parameters are accepted, not usage strategy.

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

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