explain-entity-resolution — Senzing MCP Prompt
explain-entity-resolution
is one of 31 prompts on the
Senzing
MCP server. Connect the server and it appears in your client, ready to invoke.
by client
How to invoke explain-entity-resolution from your client
- Claude Code Senzing Prompt/explain-entity-resolution run in your project directory
- Claude Desktop Senzing Prompt/explain-entity-resolution ~/Library/Application Support/Claude/claude_desktop_config.json
- Cursor Senzing Prompt/explain-entity-resolution ~/.cursor/mcp.json
- VS Code Senzing Prompt/explain-entity-resolution .vscode/mcp.json
- Zed Senzing Prompt/explain-entity-resolution ~/.config/zed/settings.json
- Windsurf Senzing Prompt/explain-entity-resolution ~/.codeium/windsurf/mcp_config.json
- Cline Senzing Prompt/explain-entity-resolution ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
- Gemini CLI Senzing Prompt/explain-entity-resolution ~/.gemini/settings.json
- Grok Senzing Prompt/explain-entity-resolution .mcp.json (in your project root)
- ChatGPT Senzing Prompt/explain-entity-resolution Settings → Connectors → Advanced → Developer mode
- Claude.ai Senzing Prompt/explain-entity-resolution Settings → Connectors → Add custom connector
- LangChain Senzing Prompt/explain-entity-resolution pip install langchain-mcp-adapters
Other prompts on this server
- analyze-data-quality
- architect-cloud-deployment
- build-a-demo
- build-entity-explorer-ui
- build-reporting-dashboard
- build-robust-error-handling
- build-scalable-loader
- build-sdk-integration
- choose-a-database
- delete-and-erase
- deployment-options
- design-er-pipeline
- evaluate-er-results
- how-would-senzing-fit
- install-senzing
- manage-redo-queue
- map-data-source
- migrate-v3-to-v4
- plan-a-poc
- plan-replication-and-ha
- platform-integration
- realtime-integration
- request-eval-license
- resolve-and-search
- run-entity-resolution
- senzing-roi
- show-me-er-in-action
- steward-entities
- troubleshoot-error
- why-senzing
Senzing also offers 2 resources — data you attach as context, where a prompt is something you run.
Read from the server itself, by connecting to it and calling prompts/list on 24 September 2026.
A listing does not declare its prompts, so asking is the only way to know them, and this
is what the server actually offers rather than what its listing claims. Names only are
stored; connect the server for each prompt's arguments.