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search_bitable_records

Query records from Feishu Bitable tables with pagination and optional filtering to retrieve specific data entries.

Instructions

    查询多维表格记录(支持分页)

    参数:
        app_token: 多维表格的token
        table_id: 数据表ID
        page_size: 每页记录数(1-500)
        page_token: 分页token,首次查询为空
        filter: (可选) 过滤条件

    返回:
        记录列表和分页信息
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_tokenYes
table_idYes
page_sizeNo
page_tokenNo
filterNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The core handler function that implements the logic for the 'search_bitable_records' tool. It queries records from a Feishu Bitable table using the Lark API, supporting pagination and optional filters.
    @mcp.tool()
    @handle_feishu_error
    def search_bitable_records(
        app_token: str,
        table_id: str,
        page_size: int = 20,
        page_token: str = "",
        filter: dict = None,
    ) -> str:
        """
        查询多维表格记录(支持分页)
    
        参数:
            app_token: 多维表格的token
            table_id: 数据表ID
            page_size: 每页记录数(1-500)
            page_token: 分页token,首次查询为空
            filter: (可选) 过滤条件
    
        返回:
            记录列表和分页信息
        """
        client = get_client()
        request_builder = (
            SearchAppTableRecordRequest.builder()
            .app_token(app_token)
            .table_id(table_id)
            .page_size(page_size)
        )
    
        if page_token:
            request_builder.page_token(page_token)
    
        body_builder = SearchAppTableRecordRequestBody.builder()
        if filter:
            # TODO: 需要根据SDK文档正确构建filter
            pass
    
        request_builder.request_body(body_builder.build())
        request = request_builder.build()
    
        response = client.bitable.v1.app_table_record.search(request)
        return lark.JSON.marshal(response.data, indent=4)
  • Registers all Bitable record tools, including 'search_bitable_records', by invoking the registration function during MCP server setup.
    # 注册多维表格工具
    register_bitable_app_tools(mcp)
    register_bitable_record_tools(mcp)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions pagination support and optional filtering, but doesn't cover important aspects like authentication requirements (app_token usage), rate limits, error conditions, whether this is a read-only operation, or what happens with invalid parameters. The description is insufficient for a tool with 5 parameters and no annotation coverage.

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 well-structured with clear sections for purpose, parameters, and returns. It's appropriately sized with no redundant information. The Chinese formatting with clear section headers makes it easy to parse, though the English translation in parentheses could be more consistent.

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 5 parameters, no annotations, but does have an output schema, the description covers the basic purpose and parameters adequately. However, for a search tool with filtering and pagination capabilities, it should provide more context about filter syntax, pagination behavior, and typical use cases. The existence of an output schema reduces the need to describe return values, but behavioral context is still lacking.

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?

With 0% schema description coverage, the description provides valuable semantic information about all 5 parameters: it explains app_token identifies the table, table_id specifies which table, page_size range (1-500), page_token usage for pagination, and filter as optional condition. This compensates well for the lack of schema descriptions, though it doesn't provide format examples for the filter object.

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 clearly states the tool's purpose as '查询多维表格记录' (search multi-dimensional table records) with the specific action '查询' (search/query) on the resource '多维表格记录' (multi-dimensional table records). It distinguishes from siblings like create/update/delete operations, though it doesn't explicitly differentiate from batch_get_bitable_records which might have similar functionality.

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 batch_get_bitable_records or other sibling tools. It mentions pagination support but doesn't explain when paginated search is preferable over batch operations or other retrieval methods.

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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