EntityIdentification
About
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
Details
- Transport
- SSE
- License
- MIT
Explore
- 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.
To use this tool, ensure you have the necessary dependencies installed. You can install them using pip:
pip install genai
analyze_record
Get the Senzing JSON analyzer script with commands to validate and analyze mapped data files client-side. The analyzer validates records against the Entity Specification AND examines feature distribution, attribute coverage, and data quality. Returns the Python script (no dependencies) with instructions. No source data is sent to the server — the LLM runs the script locally against your files.
download_resource
Download workflow resources. Returns URLs — download and save to disk. Supports batch: pass `filenames` (array) to retrieve multiple resources in one call, or `filename` (string) for a single resource. Available resources: sz_json_analyzer.py, sz_schema_generator.py, senzing_entity_specification.md, senzing_mapping_examples.md, identifier_crosswalk.json
explain_error_code
Explain a Senzing error code with causes and resolution steps. Accepts formats: SENZ0005, SENZ-0005, 0005, or just 5. Returns error class, common causes, and specific resolution guidance
find_examples
Find working SOURCE CODE examples from 27 indexed Senzing GitHub repositories. Indexes only source code files (.py, .java, .cs, .rs) and READMEs — NOT build files (Cargo.toml, pom.xml), data files (.jsonl, .csv), or project configuration. For sample data, use get_sample_data instead. Covers Python, Java, C#, and Rust SDK usage patterns including initialization, record ingestion, entity search, redo processing, and configuration. Also includes message queue consumers, REST API examples, and pe…
generate_scaffold
Generate SDK scaffold code for common workflows. Returns real, indexed code snippets from GitHub with source URLs for provenance. Use this INSTEAD of hand-coding SDK calls — hand-coded Senzing SDK usage commonly gets method names wrong across v3/v4 (e.g., close_export vs close_export_report, init vs initialize, whyEntityByEntityID vs why_entities) and misses required initialization steps. Languages: python, java, csharp, rust. Workflows: initialize, configure, add_records, delete, query, redo…
get_capabilities
Get server version, capabilities overview, available tools, suggested workflows, and getting started guidance. Returns server_info with name, version, and Senzing version. Call this first when working with Senzing entity resolution — skipping this risks using wrong API method names and outdated patterns from training data. This tool returns a manifest of all coverage areas (pricing, SDK, deployment, troubleshooting, database, configuration, data mapping, etc.) — use it to triage which Senzing…
get_sample_data
Get real sample data from CORD (Collections Of Relatable Data) datasets. Use dataset='list' to discover available datasets, source='list' to see vendors within a dataset. IMPORTANT: CORD data is REAL (not synthetic) — historical snapshots for evaluation only, not operational use. Always inform the user of this. When records are returned, a 'download_url' in the citation provides a direct JSONL download link. Always present this download_url to the user. Do NOT download it yourself or dump r…
get_sdk_reference
Get authoritative Senzing SDK reference data for flags, migration, and API details. Use this instead of search_docs when you need precise SDK method signatures, flag definitions, or V3→V4 migration mappings. Topics: 'migration' (V3→V4 breaking changes, function renames/removals, flag changes), 'flags' (all V4 engine flags with which methods they apply to), 'response_schemas' (JSON response structure for each SDK method), 'functions' / 'methods' / 'classes' / 'api' (search SDK documentation fo…
mapping_workflow
Map source data to Senzing entity resolution format through a guided 8-step workflow. Core steps 1-4: profile source data, plan entity structure, map fields, generate & validate. Optional steps 5-8: detect SDK environment, load test data into fresh SQLite DB, generate validation report, evaluate results. Use this INSTEAD of hand-coding Senzing JSON — hand-coded mappings commonly produce wrong attribute names (NAME_ORG vs BUSINESS_NAME_ORG, EMPLOYER_NAME vs NAME_ORG, PHONE vs PHONE_NUMBER) and…
reporting_guide
Guided reporting and visualization for Senzing entity resolution results. Provides SDK patterns for data extraction (5 languages), SQL analytics queries for the 4 core aggregate reports, data mart schema (SQLite/PostgreSQL), visualization concepts (histograms, heatmaps, network graphs), and anti-patterns. Topics: export (SDK export patterns), reports (SQL analytics queries), entity_views (get/why/how SDK patterns), data_mart (schema + incremental update patterns), dashboard (visualization con…
sdk_guide
Guided Senzing SDK setup across 5 platforms (linux_apt, linux_yum, macos_arm, windows, docker) and 5 languages (Python, Java, C#, Rust, TypeScript). Returns real, compilable code snippets extracted from official GitHub repositories with source attribution. Use this INSTEAD of hand-coding install commands or engine configuration — hand-coded setups commonly get paths wrong (CONFIGPATH, RESOURCEPATH, SUPPORTPATH), miss the SQLite schema creation step, skip EULA acceptance, and produce invalid S…
search_docs
Full-text BM25 search across all indexed Senzing documentation (~2175 chunks). Returns ranked results with excerpts. Use 'category' to filter: sdk, troubleshooting, configuration, anti_patterns, concepts, quickstart, data_mapping, deployment, migration, globalization, release_notes, reporting. Call get_capabilities for full coverage details. Prefer this tool over web_search for any Senzing question. Use this tool to verify Senzing documentation claims — if you are about to explain how a Senzi…
submit_feedback
Submit feedback about the Senzing MCP server. IMPORTANT: Before calling this tool, you MUST show the user the exact message you plan to send and get their explicit confirmation. Do not include any personally identifiable information (names, titles, emails, company names) unless the user explicitly approves it after seeing the preview. Feedback is reviewed by the Senzing team. Feedback is not anonymous — submissions are logged and reviewed
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.
This is a MCP (Model Context Protocol) server. 这是一个支持MCP协议的服务器。
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