Entity Identification Server

EntityIdentification is an MCP server designed to determine whether two distinct data sets belong to the same underlying entity. In many real‑world scenarios—such as customer identity verification, duplicate record detection, or data reconciliation across heterogeneous systems—developers need a reliable method to compare complex JSON objects that may differ in formatting, ordering, or minor wording variations. This server fills that gap by offering a structured comparison pipeline that blends deterministic checks with language‑model–based semantic analysis.

At its core, the server performs text normalization: all strings are lowercased, punctuation is stripped, and whitespace inconsistencies are resolved. This preprocessing step ensures that superficial differences do not obscure the true content of each field. Following normalization, value comparison occurs on a per‑field basis. For simple scalar values the server uses exact matching; for lists it disregards element order to capture unordered collections. When encountering nested or complex structures, the server recursively traverses each JSON key and applies the same comparison logic.

The most powerful aspect of EntityIdentification is its language‑model integration. After the deterministic pass, a generative model evaluates the semantic similarity of the two data sets as a whole. By feeding the aggregated comparison results into the model, it can weigh contextual clues—such as synonymous address components or alternative spellings—to produce a final judgment on entity equivalence. This hybrid approach balances precision (through exact matching) with flexibility (via semantic inference), yielding higher confidence in ambiguous cases.

Developers can leverage this server within any AI‑augmented workflow that requires entity resolution. For example, a chatbot handling user profiles can query EntityIdentification to prevent duplicate account creation; an ETL pipeline can flag records that potentially merge into a single customer; or a compliance system can audit data sharing between partners by verifying entity continuity. Because the server exposes its capabilities through MCP, it can be invoked from any AI assistant that understands the protocol, enabling seamless integration without custom client code.

Unique advantages of EntityIdentification include its model‑agnostic architecture—the language model can be swapped out or updated without changing the server logic—and its JSON‑centric design, which aligns naturally with modern APIs and data interchange formats. By abstracting the comparison logic behind a standard MCP interface, developers gain a reusable, maintainable component that enhances data quality and consistency across their applications.