What dependencies are needed to run EntityIdentification?
The server requires the `genai` Python package, which can be installed via `pip install genai`.
E
Entity Identificationn MCP Server
@u3588064
关于 Entity Identificationn MCP Server
Recognize whether two sets of data are from the same entity.
Entity Identificationn MCP Server 配置
Entity Identificationn MCP Server 工具
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工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is EntityIdentification?
EntityIdentification is an MCP server that compares two sets of data—typically JSON objects—to determine whether they originate from the same entity. It combines text normalization, exact and semantic value comparison, and a generative language model to produce a final matching judgment.
How to use EntityIdentification?
Install the required dependency (pip install genai), then call the server’s functions—normalize_text, compare_values, and compare_json—with your data. The compare_json function compares two JSON objects key-by-key and returns a result that a language model uses to decide entity identity.
Key features of EntityIdentification
- Text normalization (lowercasing, punctuation removal, whitespace normalization)
- Exact and semantic comparison of values
- List order‑agnostic comparison for arrays
- Recursive JSON key‑by‑key traversal
- Language model integration for final entity‑matching decision
Use cases of EntityIdentification
- Deduplicate customer records from separate databases
- Match product listings across different e‑commerce platforms
- Resolve identity in datasets from merged organizations
常见问题
How does EntityIdentification determine if two data sets are the same entity?
It normalizes text, compares values both exactly and semantically, traverses JSON keys, and then uses a generative language model (e.g., Gemini 2.0 Flash Thinking Exp) to produce a final match/mismatch decision.
Can EntityIdentification handle data with different key orders or missing keys?
The server compares JSON objects key by key using the provided functions; it does not specify handling of missing keys, but lists are compared ignoring element order.
What language model is used in the example?
The example code uses `genai.GenerativeModel("gemini-2.0-flash-thinking-exp")` to generate the final matching result.
Does EntityIdentification store or transmit data externally?
The README does not mention data persistence; data appears to be processed locally in memory with the language model API call.
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