// MCP TOOL REFERENCE

GOLDENMATCH TOOLS

42 tools from the GoldenMatch MCP Server, categorised by risk level.

View the GoldenMatch policy → Token cost: 3,644 tokens →

// ALL 42 GOLDENMATCH TOOLS

READ 29 tools

Read agent_compare_strategies Compare ER strategies on your data Read agent_explain_cluster Explain why records are in the same cluster Read agent_explain_pair Natural language explanation for a record pair Read agent_match_sources Match two files with intelligent strategy selection Read agent_review_queue Get borderline pairs awaiting approval Read analyze_data Profile data, detect domain, recommend ER strategy Read controller_telemetry Return the AutoConfigController telemetry from the most recent `auto_configure` or `agent_deduplicate` call... Read explain_match Explain why two records match or don't match. Shows per-field score breakdown. Read find_duplicates Find duplicate matches for a record. Provide field values to search against the loaded dataset. Read get_cluster Get details of a specific cluster: all member records and their field values. Read get_golden_record Get the merged golden (canonical) record for a cluster. Read get_stats Get dataset statistics: record count, cluster count, match rate, cluster sizes. Read identity_conflicts List evidence edges marked `conflicts_with`. Read identity_history Return the temporal event log for an identity. Read identity_list List identities, optionally filtered by dataset/status. Read identity_split Split a subset of records off an identity into a brand-new identity. The original keeps the remaining records. Read learn_thresholds Force a MemoryLearner pass over accumulated corrections. Returns the list of LearnedAdjustments produced (m... Read list_clusters List duplicate clusters found in the dataset. Returns cluster IDs, sizes, and member counts. Read list_corrections List stored Learning Memory corrections, optionally filtered by dataset. Returns id_a, id_b, decision, sour... Read list_domains List available domain extraction rulebooks (built-in + user-defined). Read match_record Match a single record against the loaded dataset in real-time. Paste a record's fields and instantly see if... Read memory_stats Return Learning Memory status: total correction count, last learn time, and current learned adjustments. Ch... Read pprl_auto_config Analyze the loaded dataset and recommend optimal PPRL (privacy-preserving record linkage) configuration. Re... Read profile_data Get data quality profile: column types, null rates, unique counts, sample values. Read scan_quality Run GoldenCheck data quality scan on a CSV file. Returns issues found (encoding errors, Unicode problems, f... Read shatter_cluster Break an entire cluster into individual records. All members become singletons. Use when a cluster is compl... Read suggest_config Analyze bad merges and suggest config changes. Provide examples of incorrect merges (pairs that should NOT ... Read suggest_pprl Check if data needs privacy-preserving matching Read test_domain Test a domain extraction rulebook against sample records. Shows what features would be extracted from the l...

WRITE 8 tools

Write add_correction Add a pair correction to Learning Memory. Source is set to 'agent' with trust=0.5 (lower than human steward... Write agent_approve_reject Approve or reject a review queue pair Write auto_configure Run AutoConfigController on a CSV; return the committed GoldenMatchConfig (incl. negative_evidence / Path Y... Write create_domain Create a custom domain extraction rulebook. Define patterns for a specific data domain (medical devices, au... Write export_results Export matching results to a file (CSV or JSON). Write identity_merge Manually merge two identities. All records from `absorb_entity_id` are reassigned to `keep_entity_id`. Write identity_resolve Resolve a record_id to its durable identity. Returns the full identity view (members, evidence edges, recen... Write memory_export Return all corrections as a list of dicts (CSV-shaped). Caller is responsible for writing the file. Optiona...

DESTRUCTIVE 1 tools

Destructive unmerge_record Remove a record from its cluster. The record becomes a singleton. Remaining cluster members are re-clustere...

EXECUTE 4 tools

Execute agent_deduplicate Run full ER pipeline with confidence gating and reasoning Execute fix_quality Run GoldenCheck scan and apply fixes to a CSV file. Returns the fixed data summary and a manifest of all fi... Execute pprl_link Run privacy-preserving record linkage between two parties' data. Computes bloom filters, matches records wi... Execute run_transforms Run GoldenFlow data transforms on a CSV file. Normalizes phone numbers (E.164), dates (ISO), categorical sp...

// RUNNING THIS SERVER

The managed route: connect GoldenMatch through the PolicyLayer gateway — every tool call above is checked against your policy before it runs, with a full audit log.

DIRECT INSTALL (UNMANAGED) npx -y pypi:goldenmatch

// FAQ

How many tools does the GoldenMatch MCP server have? +

The GoldenMatch MCP server exposes 42 tools across 4 categories: Read, Write, Destructive, Execute.

How do I enforce policies on GoldenMatch tools? +

Route the GoldenMatch server through the PolicyLayer gateway. Define allow, deny, or approval rules per tool in the dashboard — they are enforced on every call before it reaches the server.

What risk categories do GoldenMatch tools fall into? +

GoldenMatch tools are categorised as Read (29), Write (8), Destructive (1), Execute (4). Each category has a recommended default policy.

Let agents act without letting them run wild.

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