MCP Server

GoldenMatch provides an MCP (Model Context Protocol) server for integration with Claude Desktop and other MCP-compatible AI assistants.

Remote Server (no install required)

GoldenMatch is available as a hosted remote MCP server on Smithery. Connect from Claude Desktop, Claude Code, or any MCP client without installing anything locally.

Add to your claude_desktop_config.json:

{
    "mcpServers": {
        "goldenmatch": {
            "url": "https://goldenmatch-mcp-production.up.railway.app/mcp/"
        }
    }
}

Or browse on Smithery: https://smithery.ai/servers/benzsevern/goldenmatch

Local Server

Start the server 

pip install goldenmatch[mcp]
goldenmatch mcp-serve --file customers.csv --config config.yaml
# Or with HTTP transport:
goldenmatch mcp-serve --file customers.csv --transport http --port 8200

Or add to your Claude Desktop configuration (claude_desktop_config.json):

{
    "mcpServers": {
        "goldenmatch": {
            "command": "goldenmatch",
            "args": ["mcp-serve", "--file", "customers.csv"]
        }
    }
}

With a config file:

{
    "mcpServers": {
        "goldenmatch": {
            "command": "goldenmatch",
            "args": ["mcp-serve", "--file", "customers.csv", "--config", "config.yaml"]
        }
    }
}

Tools

The MCP server exposes the following tools to Claude Desktop:

get_stats

Get dataset statistics: record count, cluster count, match rate, cluster sizes.

"How many duplicates did you find?"

find_duplicates

Search for duplicate records matching a query.

"Find duplicates of John Smith"

get_cluster

Get details of a specific cluster including all member records and pair scores.

"Show me cluster 42"

match_record

Match a new record against the loaded dataset.

"Does this record match anything: name=Jane Doe, email=jane@example.com?"

explain_match

Explain why two specific records were matched or not matched.

"Why were records 42 and 108 matched?"

unmerge_record

Remove a record from its cluster. Re-clusters the remaining members.

"Remove record 215 from its cluster, it was a false match"

suggest_config

Analyze bad merges, identify which fields caused false matches, and suggest threshold/weight changes.

"Cluster 5 has a bad merge. What should I change?"

list_domains

List all available domain packs (built-in and custom).

"What domain packs are available?"

create_domain

Create a new custom domain pack.

"Create a domain pack for automotive parts with fields: part_number, manufacturer, fitment"

test_domain

Test a domain pack against sample data to verify extraction quality.

"Test the electronics domain pack on my data"

pprl_auto_config

Analyze data and recommend optimal PPRL parameters.

"What PPRL settings should I use for this dataset?"

Run privacy-preserving record linkage.

"Link hospital_a.csv and hospital_b.csv using PPRL"

How it works

When the MCP server starts, it:

  1. Loads data from the specified file(s)
  2. Loads or auto-generates a matching configuration
  3. Runs the full matching pipeline
  4. Caches results in memory
  5. Exposes tools via the MCP protocol over stdio

The server uses the MatchEngine from goldenmatch.tui.engine (which has no Textual dependency) for matching operations.

Example conversation

With Claude Desktop connected to the GoldenMatch MCP server:

You: “How many duplicates are in my customer data?”

Claude: Uses get_stats tool. “Your dataset has 5,000 records with 847 duplicate clusters. The match rate is 12%, meaning about 600 records are duplicates.”

You: “Show me the biggest cluster”

Claude: Uses get_cluster tool. “Cluster 14 has 8 members. Here are the records: [table of members with field values and pairwise scores]”

You: “Record 215 doesn’t belong there, remove it”

Claude: Uses unmerge_record tool. “Done. Record 215 has been removed from cluster 14. The remaining 7 records have been re-clustered.”

You: “The name matching is too aggressive. What should I change?”

Claude: Uses suggest_config tool. “The jaro_winkler threshold for first_name is 0.80, which is catching partial matches like ‘John’ and ‘Jonathan’. I suggest raising it to 0.88 and adding a last_name exact match as a secondary check.”

Auto-config mode

If no config file is specified, the MCP server auto-configures matching rules:

goldenmatch mcp-serve --file customers.csv

Auto-config detects column types, assigns appropriate scorers, and picks a blocking strategy. The suggest_config tool can then help refine the auto-generated config based on observed results.