snw-derived-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@snw-derived-mcp 为广告组分析广告活动状态并生成派生属性"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
snw-derived-mcp
Agent Native 的派生属性 MCP 服务。外部 Agent 提交“目标对象 + 字段需求”,服务在 Amazon Ads mock 本体的三跳邻域内确定来源字段、校验 Link 基数、生成 Semantic Join SQL,并可创建和执行只读派生属性。
核心规则
全链路
to-one直接投影;任一跳to-many必须聚合。支持 1:1、1:N 和带 junction table 的 M:N Link;M:N 双向均视为
many。支持 Count、Sum、Avg、Min、Max、去重计数、Collect List/Set。
路径最多三跳,超出返回
OUT_OF_NEIGHBORHOOD。普通 Derived 拒绝过滤、排序和“取最新一条”。
SQL 流程为
seed → semi-select → 根键传播 → 聚合 → LEFT JOIN 回根对象。DuckDB 可执行;Spark/Hive 可生成
LEFT SEMI JOIN预览。
Related MCP server: Glossary MCP Server
运行
uv sync
uv run snw-derived-mcp --database var/snw-derived.duckdbMCP 客户端配置示例:
{
"mcpServers": {
"snw-derived": {
"command": "uv",
"args": ["--directory", "/absolute/path/snw-derived-mcp", "run", "snw-derived-mcp"]
}
}
}外部 Agent 调用顺序
snw_list_object_typessnw_get_object_neighborhoodsnw_analyze_field_request仅当结果为
READY时,将返回的plan、ontology_version、plan_digest原样传给snw_create_derived_property;同名更新必须显式设置replace_existing=truesnw_execute_derived_property验证 mock 数据结果
示例:object_type="广告组"、request="广告活动状态" 会定位到 AdGroup → Campaign.status,判断为全程 to-one,无聚合,建议字段名 campaign_status。
M:N 示例:object_type="广告活动"、request="标签名称列表" 会沿 Campaign ↔ Label 的 junction table 生成 Collect List 计划。
验证
uv run ruff check .
uv run mypy src
uv run pytest -q
uv build本项目不连接 Palantir、真实 Amazon Ads 或生产数仓;实现的是本仓库规格锁定的 Derived 语义演示。
Available Tools
6 toolssnw_analyze_field_requestC
在三跳邻域内解析字段来源、校验基数,并生成不可变语义计划和 SQL。
Inputs: request (required), object_type (required), dialect, aggregation, +3 more. Returns: object
snw_create_derived_propertyB
持久化只读派生属性;同名替换必须显式设置 replace_existing。
Inputs: plan (required), plan_digest (required), ontology_version (required), property_api_name (required), +1 more. Returns: object
snw_execute_derived_propertyC
在本地 Amazon Ads mock 数据上执行已注册派生属性。
Inputs: target_object (required), property_api_name (required), object_ids. Returns: object
snw_get_object_neighborhoodA
返回对象在最多三跳内的全部无环 Link 路径及每跳基数。
Inputs: object_type (required), max_hops. Returns: object
snw_list_derived_propertiesA
列出已创建派生属性及完整可审计语义计划。
Inputs: no named parameters. Returns: object
snw_list_object_typesA
列出可作为派生字段根对象的对象类型。
Inputs: no named parameters. Returns: object
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 6 tools
Each tool targets a distinct resource or action: object type enumeration, graph neighborhood exploration, execution, analysis/planning, creation, and listing. There is no meaningful overlap that would cause an agent to confuse one tool with another.
All tools share a consistent snw_ prefix and follow a clear verb_noun pattern. The minor singular/plural variation (derived_property vs derived_properties) is standard and does not create confusion.
Six tools is well-scoped for the derived-property workflow. Each tool covers a distinct step in the lifecycle without unnecessary redundancy or bloat.
The server covers exploration, analysis, execution, creation/replacement, and listing of derived properties. The only notable gap is the lack of an explicit delete/drop operation, though replace_existing covers updates and the core workflow is otherwise complete.
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