MCP 服务器

EntityIdentification

A MCP server that helps determine if two sets of data belong to the same entity by comparing both exact and semantic equality through text normalization and language model integration.

README

EntityIdentification

Identify whether two sets of data are from the same entity. 识别两组数据是否来自同一主体

This is a MCP (Model Context Protocol) server. 这是一个支持MCP协议的服务器。

Data Comparison Tool

This tool provides a comprehensive way to compare two sets of data, evaluating both exact and semantic equality of their values. It leverages text normalization and a language model to determine if the data originates from the same entity.

Features

Text Normalization: Converts text to lowercase, removes punctuation, and normalizes whitespace.
Value Comparison: Compares values directly and semantically (ignoring order for lists).
JSON Traversal: Iterates through each key in the JSON objects and compares corresponding values.
Language Model Integration: Uses a generative language model to assess semantic similarity and provide a final judgment on whether the data comes from the same entity.

Installation

To use this tool, ensure you have the necessary dependencies installed. You can install them using pip:

pip install genai

Usage

Functions

normalize_text(text):
- Normalizes the input text by converting it to lowercase, removing punctuation, and normalizing whitespace.
compare_values(val1, val2):
- Compares two values both exactly and semantically.
- If the values are lists, it ignores the order of elements for semantic comparison.
compare_json(json1, json2):
- Compares two JSON objects key by key.
- Uses compare_values to evaluate each key's values.
- Integrates a language model to assess semantic similarity and provides a final judgment.

Example

import json
import genai
import re

# Define your JSON objects
json1 = {
    "name": "John Doe",
    "address": "123 Main St, Anytown, USA",
    "hobbies": ["reading", "hiking", "coding"]
}

json2 = {
    "name": "john doe",
    "address": "123 Main Street, Anytown, USA",
    "hobbies": ["coding", "hiking", "reading"]
}

# Compare the JSON objects
comparison_results = compare_json(json1, json2)

# Generate final matching result
model1 = genai.GenerativeModel("gemini-2.0-flash-thinking-exp")
result_matching = model1.generate_content("综合这些信息，你认为可以判断两个数据来自同一主体吗？"+json.dumps(comparison_results, ensure_ascii=False, indent=4))
print(result_matching.text)