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2025-03-21

MCP (Model Context Protocol) server for identifying whether two sets of data are from the same entity. 识别两组数据是否来自同一主体的MCP服务器

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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

  1. normalize_text(text):

    • Normalizes the input text by converting it to lowercase, removing punctuation, and normalizing whitespace.
  2. 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.
  3. 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)

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

If you have any questions or suggestions, please contact me:

Wechat qrcode_for_gh_643efb7db5bc_344(1)

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    Reviews

    1 (1)
    Avatar
    user_2YuJkPtg
    2025-04-15

    The Calculator MCP Server by mvavassori is an absolute game-changer for anyone needing reliable and efficient computational power. The performance is top-notch, and the server handles complex calculations with ease. Highly recommend this product to anyone in need of a robust and dependable calculation tool. Check it out here: https://mcp.so/server/calculator-mcp-server/mvavassori.