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lloydzhou

Bitable MCP Server

by lloydzhou

list_table

Retrieve all tables from your current Bitable workspace to view and manage your data structure.

Instructions

list table for current bitable

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function list_table executes the tool logic: connects to the bitable database pool, creates a cursor, runs 'show tables' query, fetches results, and returns them as JSON string.
    def list_table() -> list[str]:
        with conn_pool.connect() as connection:
            logger.error("connection %r", connection)
            logger.error("bot %r", connection.bot)
            logger.error("bot %r", connection.bot.personal_base_token)
            cursor = connection.cursor()
            tables = cursor.execute('show tables').fetchall()
            return json.dumps(tables)
  • The @mcp.tool decorator registers the list_table function as a tool named 'list_table' with its description.
    @mcp.tool(
        name="list_table",
        description="list table for current bitable",
    )
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 only states the action ('list table') without details on permissions, rate limits, pagination, or what 'current bitable' entails. This is inadequate for a tool with zero annotation coverage, as it lacks critical 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 description is a single phrase ('list table for current bitable'), which is concise but potentially under-specified. It lacks structure or front-loading of key details, making it efficient but not optimally informative for an agent.

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

Completeness2/5

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

Given the tool's simplicity (0 parameters, no output schema), the description is incomplete. It doesn't explain what 'current bitable' means, how results are returned, or differentiate from siblings, leaving gaps in context despite low complexity.

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

Parameters4/5

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

The tool has 0 parameters, and the schema description coverage is 100% (though empty). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for tools with no parameters, as there's nothing to compensate for.

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

Purpose3/5

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

The description states the tool's purpose as 'list table for current bitable', which clearly indicates a listing operation on tables. However, it doesn't specify what 'current bitable' means or how this differs from sibling tools like 'describe_table' and 'read_query', making it somewhat vague about scope and differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives like 'describe_table' or 'read_query'. It doesn't mention any prerequisites, context for 'current bitable', or exclusions, leaving the agent without usage instructions.

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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