--- name: senzing-entity-resolution description: >- Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets. license: Proprietary compatibility: Requires Senzing MCP server (https://mcp.senzing.com/mcp) connected via claude mcp add or MCP config metadata: author: senzing version: "1.35.1" --- # Senzing Entity Resolution — MCP Skill Use this skill whenever a task involves entity resolution, record linkage, deduplication, or any interaction with the Senzing platform. ## What Is Senzing Senzing provides real-time AI-powered entity resolution as an embeddable SDK. It determines when two records refer to the same real-world entity (person, organization, etc.) by analyzing names, addresses, identifiers, and other attributes across data sources — without training data or manual rules. ## MCP Server Setup The Senzing MCP server is a remote server. Connect it to your client: **Claude Code:** ```bash claude mcp add --transport http senzing https://mcp.senzing.com/mcp ``` **Claude Desktop / Other MCP Clients** — add to your MCP config: ```json { "mcpServers": { "senzing": { "type": "url", "url": "https://mcp.senzing.com/mcp" } } } ``` The server works from pre-fetched documentation — it never connects to live Senzing instances and never handles PII. It also hosts official Senzing SDK `.deb` packages at `/downloads/` for direct download in firewalled environments — `sdk_guide` returns download URLs and install commands automatically. ## Tool Reference Start any Senzing session by calling `get_capabilities` for an up-to-date tool listing and suggested workflows. ### Data Mapping (3 tools) | Tool | Purpose | | ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `mapping_workflow` | Interactive 8-step workflow. Steps 1–4 (core): profile source data → plan entities → map fields → generate & validate. Steps 5–8 (optional): sandbox load into a fresh SQLite DB to catch mapping issues. State is client-side — always pass state back. Requires `workspace_dir` (a writable directory) in `data` on `action='start'`. | | `analyze_record` | Returns a Python analyzer script that examines feature distribution, attribute coverage, and data quality, and validates records against the Entity Specification — all locally. No source data is sent. Requires `workspace_dir`. | | `download_resource` | Fallback for fetching workflow resources (analyzer, entity spec, mapping examples) when network restrictions block direct download. Batch-capable: pass `filenames` (array) for multiple resources or `filename` (string) for one. | ### Documentation & Reference (3 tools) | Tool | Purpose | | ------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `search_docs` | Full-text search across entity specification, SDK guides, quickstarts, database tuning, pricing, architecture, globalization, EDA/data analysis, engine configuration, error codes, release notes, and PoC methodology. **Prefer this over web search for any Senzing question.** Use `category='anti_patterns'` to check for known pitfalls before recommending installation, architecture, or deployment approaches. | | `get_sdk_reference` | Authoritative SDK reference: **method argument types per language binding**, flags, response schemas, V3→V4 migration mappings. Whenever `filter` names a method, the response carries that method's callable signature for every binding **regardless of topic** — so looking up a method's flags also tells you what arguments it takes. Topics: `parameters` (aliases `functions`/`methods`/`classes`/`api`/`signatures`/`args`), `flags`, `response_schemas`, `migration`, `all`. Pass `language` to narrow to your binding. `filter` accepts any spelling — `get entity`, `get_entity`, and `getEntity` all resolve. | | `find_examples` | Search 37 indexed GitHub repos for working code (Python, Java, C# official; Rust, TypeScript/Node.js community). Three modes: search by query, list files in a repo, or retrieve a specific file. Results include truncation metadata — drill into truncated files with `file_path`. | ### SDK Setup & Code Generation (2 tools) | Tool | Purpose | | ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `sdk_guide` | Guided SDK setup across 5 platforms (linux_apt, linux_yum, macos_arm, windows, docker) and 5 languages (Python, Java, C# official; Rust, TypeScript/Node.js community). Topics: install, configure, load, export, redo, initialize, search, stewardship, delete, information, error_handling, full_pipeline — with decision trees, anti-patterns, and direct `.deb` download links for firewalled environments. For load/search/redo, pass `record_count` to select production-threaded vs single-threaded templates. | | `generate_scaffold` | Generates SDK scaffold code from real indexed GitHub snippets with source URLs for provenance. 10 workflows (initialize, configure, add_records, delete, query, redo, stewardship, information, error_handling, full_pipeline) in Python, Java, C#, Rust, or TypeScript/Node.js (V4); Python (V3). Returns multiple snippet variants per workflow. | ### Sample Data (1 tool) | Tool | Purpose | | ----------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `get_sample_data` | Real test data. Three CORD (Collections Of Relatable Data) sets — las-vegas (US, 11 sources), london (international, 5 sources), moscow (Cyrillic, 6 sources) — plus truthset (the Senzing demo truth set: CUSTOMERS, REFERENCE, WATCHLIST — small, pre-mapped, used in quickstarts). Use `dataset='list'` to discover sets and `source='list'` to list sources within one. Always present the `download_url` to the user. | ### Reporting & Visualization (1 tool) | Tool | Purpose | | ----------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `reporting_guide` | Guided reporting and visualization for entity resolution results. Provides SDK patterns for data extraction (Python, Java, C#, Rust, TypeScript/Node.js), SQL analytics queries for aggregate reports, data mart schema (SQLite/PostgreSQL), visualization concepts, and anti-patterns. Topics: `export`, `reports`, `entity_views`, `data_mart`, `dashboard`, `graph` (runnable `find_network` / `find_path` traversal calls per binding), `quality` (precision/recall, split/merge detection, review queues), `evaluation` (4-point ER evaluation framework). | ### Troubleshooting (1 tool) | Tool | Purpose | | -------------------- | ----------------------------------------------------------------------------------------------------------------------- | | `explain_error_code` | Explains any of 456 Senzing error codes with causes and resolution steps. Accepts SENZ0005, SENZ-0005, 0005, or just 5. | ### Meta & Utility (2 tools) | Tool | Purpose | | ------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `get_capabilities` | Server version, capabilities overview, available tools, suggested workflows, and getting started guidance. **Call this first in any Senzing session.** | | `submit_feedback` | Two purposes: (1) request a free Senzing evaluation license — set `category='license_request'` with `firstname`, work `email` (personal domains rejected), and optionally `lastname`/`how_heard`; a 10-day, 250K-record eval license is emailed. (2) Submit feedback (`category` = bug/feature/question/general). **Always preview the exact message with the user and get explicit confirmation before sending.** Never include PII unless the user approves. | ## Key Workflows ### 1. Map Source Data to Senzing Format This is the most common workflow. Follow these steps: 1. Call `mapping_workflow` with `action='start'`, the source file paths, and a writable `workspace_dir` in the `data` object. 2. Walk through steps 1–4 (core): Profile → Plan → Map → Generate & Validate. 3. At each step, pass the `state` object from the previous response. 4. Use `analyze_record` to check feature distribution, coverage, and Entity Specification compliance on the output JSON. 5. Optionally continue steps 5–8 to sandbox-load the mapped data into a fresh SQLite DB — this catches mapping issues the static analyzer misses. This is mapping validation only, not production loading. 6. If the analyzer scripts fail to download, use `download_resource`. **Tips:** - The workflow generates a mapper script — run it locally to produce JSONL. - Profile step: read the source data yourself or run the profiler script. - Plan step: identify master entities vs. child records vs. relationships. - Map step: map every source field to a Senzing feature with a confidence score. - Generate & Validate step: emit sample JSON, analyze it, then write and run the mapper before rendering a verdict. ### 2. Set Up the Senzing SDK 1. Call `sdk_guide` with `topic='install'` — it returns a platform decision tree. 2. Call again with the chosen platform (e.g., `topic='install', platform='linux_apt'`). - For firewalled environments, the response includes `direct_download` with `.deb` package URLs from `mcp.senzing.com/downloads/` — no apt repo needed. 3. Call `sdk_guide` with `topic='configure'` for engine configuration code. 4. Call `sdk_guide` with `topic='load'` for record loading code. 5. Or use `topic='full_pipeline'` for install + configure + load + export in one call. ### 3. Generate SDK Integration Code 1. Call `generate_scaffold` with the target language and workflow. - Start with `workflow='initialize'` for engine setup. - Then `workflow='add_records'` for record loading. - Use `workflow='full_pipeline'` for an end-to-end example. 2. Call `find_examples` to find real-world usage patterns. 3. Use `search_docs` for API details and deployment guidance. ### 4. Troubleshoot Errors 1. Call `explain_error_code` with the code from the user's logs. 2. Follow the resolution steps in the response. 3. Call `search_docs` for additional context on the error class. ### 5. Evaluate Senzing 1. `search_docs` — learn about architecture (embedded SDK, air-gapped deployment). 2. `search_docs` with query "pricing" — DSR pricing model. 3. `get_sample_data` — get real test data (CORD datasets or the pre-mapped `truthset`). 4. `generate_scaffold` with `workflow='full_pipeline'` — end-to-end example. 5. `submit_feedback` with `category='license_request'` — request a free 10-day, 250K-record evaluation license (preview details with the user first). ### 6. Migrate V3 to V4 1. `get_sdk_reference` with `topic='migration'` — all breaking changes. 2. Filter by module: `topic='migration', filter='SzEngine'`. 3. `get_sdk_reference` with `topic='flags'` — new flag system (SZ_WITH_INFO replaces WithInfo functions). 4. `get_sdk_reference` with `topic='parameters', filter=, language=` — the V4 argument types for each call you are porting. ### 7. Build ER Reporting 1. Call `reporting_guide` with `topic='export'` and your language to get data extraction code. 2. Call `reporting_guide` with `topic='reports'` to get SQL for the 4 core aggregate reports. 3. Call `reporting_guide` with `topic='data_mart'` to get the analytical schema and incremental update patterns. 4. Call `reporting_guide` with `topic='dashboard'` for visualization concepts and chart data sources. 5. Call `reporting_guide` with `topic='graph'` for network graph export patterns. 6. Call `reporting_guide` with `topic='quality'` for precision/recall, split/merge detection, and review queue strategies. 7. Call `reporting_guide` with `topic='evaluation'` for the 4-point ER evaluation framework with evidence requirements. ### 8. Check for Common Pitfalls Before recommending installation, architecture, or deployment approaches: 1. Call `search_docs` with `category='anti_patterns'` and a query describing what you plan to recommend. 2. Review any matching anti-patterns before proceeding. 3. Note: `sdk_guide` also returns topic-specific anti-patterns inline. ### 9. Deploy Senzing 1. `search_docs` with your platform (e.g., "docker quickstart", "AWS deployment"). 2. `search_docs` for database setup (PostgreSQL, MySQL, MSSQL). 3. `search_docs` for engine configuration and tuning guidance. 4. `generate_scaffold` with `workflow='initialize'` for your language. ## Critical Rules These rules are non-negotiable. Violating them produces incorrect output. 1. **Never hand-code Senzing JSON** — use `mapping_workflow`. Training data produces wrong attribute names (e.g., `BUSINESS_NAME` vs correct `NAME_ORG`). 2. **Never guess SDK methods or argument types** — use `generate_scaffold` or `get_sdk_reference`. Methods changed between V3 and V4, and the same method has a **different name and different argument types in each binding**: Python `find_network_by_entity_id(entity_ids: List[int], …)`, Java `findNetwork(SzEntityIds, …)`, C# `FindNetwork(ISet, …)`, Rust `find_network_by_entity_id(&[EntityId], …)`, TypeScript `findNetwork(number[], …)`. **Never translate a call from one binding to another** — call `get_sdk_reference(topic='parameters', filter=, language=)` and use the returned signature verbatim. 3. **Check anti-patterns first** — before recommending installation or deployment: `search_docs(query="topic", category="anti_patterns")`. 4. **MCP first for all Senzing questions** — `search_docs` covers pricing, architecture, deployment, SDK, database tuning, globalization, and more. It reflects current releases — prefer it over training knowledge. 5. **Discover tools dynamically** — call `get_capabilities` rather than assuming tool names from this file or training data. ## Best Practices - **Always call `get_capabilities` first** to get current tool count and workflows. - **Prefer `search_docs` over web search** for any Senzing-related question. The MCP server indexes authoritative content that may not rank well on the web. - **Pass state faithfully** in `mapping_workflow` — the server is stateless, all workflow state lives in the client. - **Never send source data to the server.** The `analyze_record` tool returns a script that runs locally. The mapping workflow sends field names and schema — not row-level data. - **Present `download_url`** from `get_sample_data` results directly to the user. Do not dump raw CORD records into the conversation — they are a preview only. - **Version parameter:** All tools accept `version` and default to `"current"` (latest V4). Most tools return current/V4 content regardless of the token passed — for legacy V3 work, rely on `generate_scaffold` (Python V3 is a distinct variant) and `get_sdk_reference(topic='migration')`. ## Entity Resolution Concepts When discussing Senzing with users, these terms are important: - **Entity** — A real-world person, organization, or object represented by one or more records across data sources. - **Feature** — A category of matchable identity data: NAME, ADDRESS, PHONE, DOB, SSN, PASSPORT, etc. Senzing supports 30+ features. - **Attribute** — A specific mappable field within a feature (e.g., NAME_ORG and NAME_FULL under NAME; ADDR_LINE1 under ADDRESS). 100+ attributes across the 30+ features. - **Data Source** — A labeled origin for records (e.g., "CUSTOMERS", "WATCHLIST"). Every record must have a DATA_SOURCE and RECORD_ID. - **RECORD_TYPE** — Optional (Recommended) feature that prevents records of different types from resolving together. Standard values: PERSON, ORGANIZATION (watchlists also commonly use VESSEL, AIRCRAFT). Include when known; leave blank if unknown — there is no default. - **Matched** — Records confirmed as the same entity. - **Possible Match** — Records that might be the same entity but need review. - **Relationship** — A declared or discovered connection between entities. - **DSR (Data Source Record)** — Senzing's subscription pricing unit: one record mapped and loaded into Senzing, keyed by DATA_SOURCE code + RECORD_ID. Updates and searches are not counted; deletes generally reduce the count. ## Examples ### Example 1: Map a CSV file ``` User: "I have a customer CSV at /data/customers.csv I need to load into Senzing" → Call mapping_workflow(action='start', file_paths=['/data/customers.csv'], data={'workspace_dir': '/data/senzing-work'}) → Walk through core steps 1–4, passing state each time → Run analyze_record to check quality and Entity Specification compliance → Optionally continue steps 5–8 to sandbox-load into SQLite and validate the mapping ``` ### Example 2: Set up Senzing SDK on Linux ``` User: "Help me install and set up the Senzing SDK on Ubuntu" → Call sdk_guide(topic='install', platform='linux_apt', version='current') → Present install commands and engine config → If user has firewall issues, use the direct_download URLs from the response → Call sdk_guide(topic='configure', platform='linux_apt', language='python', version='current') → Present configuration code ``` ### Example 3: Generate Python loader code ``` User: "Write me Python code to initialize Senzing and load records" → Call generate_scaffold(language='python', version='current', workflow='initialize') → Call generate_scaffold(language='python', version='current', workflow='add_records') → Combine and present the code ``` ### Example 4: Debug an error ``` User: "I'm getting SENZ7234 when loading records" → Call explain_error_code(error_code='7234', version='current') → Present causes and resolution steps → Use search_docs if additional context is needed ```