Company Name Fuzzy Match & Normalization
omnial/x402-company-name-match
Given two company names, normalizes each (stripping corporate suffixes like Inc/Incorporated, Ltd/Limited, GmbH, AB/Aktiebolag) and returns whether they match, a 0-to-1 confidence score, the normalized form of each name, which suffixes were removed from each, and the individual Levenshtein, Jaro-Winkler, and token-overlap similarity scores behind the confidence figure.
Price
Up to $0.0325 per call; you pay what the call used
You pay the price shown. If a call turns out to cost more than its quote, you pay the actual price, capped at twice the quote. No monthly minimum. Top-ups start at $5.00.
Data source
Computed by Eden Engine from the inputs you provide.
Use it
Your AI assistant does the work: it finds this tool, shows you the price first, runs it, and you are charged when the run finishes. There is nothing to set up for this tool in particular.
Connect once and your AI can find and run this tool, and any other it needs.
For developers: the calls your assistant makes
// 1. search: find the tool
omnial_search({ query: "what you need" })
// 2. inspect: price and input schema
omnial_inspect({ tool: "omnial/x402-company-name-match" })
// 3. learn: read the usage guide at runtime
omnial_learn({ tool: "omnial/x402-company-name-match" })
// 4. run: price the exact call first, then run it
omnial_execute({ tool: "omnial/x402-company-name-match", input: { /* see input_schema */ }, dry_run: true })
omnial_execute({ tool: "omnial/x402-company-name-match", input: { /* ... */ } })
// 5. settle: the call is charged when it finishes, nothing to doNot connected yet? Point your MCP client at https://mcp.eden-engine.com/mcp, then copy a config for your client.
Pricing
Every charge this tool can incur.
| Charge | Price |
|---|---|
Per call | $0.0325 |
- Updated
- Oct 27, 2026
Input and output schemas
Input schema
{
"type": "object",
"required": [
"name_b",
"name_a"
],
"properties": {
"name_a": {
"type": "string",
"description": "First company name"
},
"name_b": {
"type": "string",
"description": "Second company name to compare"
}
},
"additionalProperties": false
}Output schema
{
"type": "object",
"properties": {
"match": {
"type": "boolean",
"description": "Whether the two names are judged to refer to the same company."
},
"name_a": {
"type": "string",
"description": "The first company name exactly as submitted, echoed back."
},
"name_b": {
"type": "string",
"description": "The second company name exactly as submitted, echoed back."
},
"confidence": {
"type": "number",
"description": "Match confidence, 0 to 1. Observed 1 on an exact match after normalization ('Apple' vs 'Apple Inc.') and 0.2 on two genuinely unrelated companies -- treat as a graded score, not a pass/fail flag."
},
"normalized_a": {
"type": "string",
"description": "`name_a` lowercased with corporate suffixes and punctuation stripped."
},
"normalized_b": {
"type": "string",
"description": "`name_b` lowercased with corporate suffixes and punctuation stripped."
},
"suffixes_removed": {
"type": "object",
"properties": {
"a": {
"type": "array",
"items": {
"type": "string"
}
},
"b": {
"type": "array",
"items": {
"type": "string"
}
}
},
"description": "The corporate suffix tokens (e.g. 'inc', 'ltd') stripped from each name while normalizing, lowercased. Observed empty on a name with no suffix to strip.",
"additionalProperties": true
},
"similarity_scores": {
"type": "object",
"properties": {
"levenshtein": {
"type": "number"
},
"jaro_winkler": {
"type": "number"
},
"token_overlap": {
"type": "number"
}
},
"description": "The individual algorithm scores `confidence` is derived from, each roughly 0 to 1.",
"additionalProperties": true
}
},
"description": "The company-name comparison result.",
"additionalProperties": true
}