Why I built a deterministic Apollo → Salesforce mapper instead of using an LLM

There are roughly 4,000 MCP servers on Smithery right now. Most of them wrap an LLM prompt around an API call and call it a "tool." For a lot of tasks that's fine. For data mapping into a production CRM, it's a liability.

Here's what happened when I asked GPT-4o to map an Apollo contact export to a Salesforce Lead object: it got FirstName and LastName right. It got Email right. Then it invented a field called LeadPhone (Salesforce uses Phone), formatted the number as (415) 555-1234 instead of the E.164 +14155551234 that lookup deduplication expects, and quietly dropped MobilePhone entirely because "it wasn't in the example."

That last part is the killer. LLMs silently omit fields they're uncertain about. You don't get an error. You get a lead record with a blank mobile number and a phone field that fails the dedup match three months later when the same person comes in through a different source.

The deterministic alternative

I built apollo-salesforce-mapper — a Cloudflare Worker that maps the full Apollo CSV export surface to Salesforce Lead objects using hardcoded TypeScript rules. No LLM in the loop. No inference. No "I think this might be the right field."

The contract covers 33 Apollo input fields → 21 Salesforce output fields:

• Names: first_name, last_name, or compound full_name → split deterministically (handles "Jr.", "III", hyphenated last names)
• Phones: cell, mobile, work_phone, corporate_phone → E.164 normalisation (US 10-digit, US 11-digit, international)
• Address: city, state, country, postal_code, street_address → direct passthrough
• Company signals: annual_revenue ($50M, 50000000), number_of_employees (500-1000, "500 to 1000"), industry → normalised
• Custom: linkedin_url → LinkedIn__c, twitter_url → Twitter__c

The receipt format: PASS / REPAIR / FAIL

Every call returns a Deterministic Receipt — not just the mapped data, but a complete audit trail of every transformation:

{
  "verdict": "REPAIR",
  "receipt": {
    "task_id": "sha256:a3f...",
    "confidence": 0.95,
    "diff": [
      {
        "field": "Phone",
        "input": "4155551234",
        "output": "+14155551234",
        "rule": "e164_us10digit",
        "confidence": 0.95
      },
      {
        "field": "AnnualRevenue",
        "input": "$50M",
        "output": 50000000,
        "rule": "revenue_parse",
        "confidence": 0.85
      }
    ]
  },
  "data": {
    "FirstName": "Jane",
    "LastName": "Doe",
    "Phone": "+14155551234",
    "Email": "jane@acme.com",
    ...
  }
}

PASS means the data arrived clean — no transformation needed, confidence 1.0 across the board. REPAIR means normalisation was applied (phone formatting, revenue parsing, name splitting). FAIL means a required field — FirstName, LastName, or Phone — couldn't be resolved. It never silently corrupts data.

It runs as an MCP tool

The server exposes a single tool: apollo_to_salesforce_lead. Add it to Claude Desktop in 30 seconds:

{
  "mcpServers": {
    "apollo-salesforce-mapper": {
      "type": "streamableHttp",
      "url": "https://cf-worker.selbyventurecap.workers.dev/mcp"
    }
  }
}

Then you can say: "Map this Apollo contact to a Salesforce Lead" and paste the raw export data. Claude passes it to the tool, gets the PASS/REPAIR/FAIL receipt, and can tell you exactly what was normalised before it hits your CRM.

The payment model: $0.01 USDC on Base Mainnet

The /map endpoint uses x402 — the HTTP payment standard. Any x402-compatible agent sends a signed USDC transaction as part of the request header. The CDP facilitator verifies and settles it on Base Mainnet before the response is returned. No billing setup. No API keys. No invoices.

The /mcp and /contracts endpoints are free. Only the payment-gated HTTP endpoint costs anything. And idempotency caching means identical payloads replay free for 24 hours — so bulk re-processing after a schema change doesn't cost per-record.

Why not just use a Zapier zap?

You can, and it's a valid pattern. But the advantage here is the receipt format. A Zapier field mapper tells you "it ran." This tells you what it changed and with what confidence. If you're importing 50,000 Apollo contacts into Salesforce, knowing that 12% needed phone normalisation and 0.3% failed on missing last names is operationally useful data before you commit to the import.

The server is live, open to any MCP client, and listed on Smithery. The free /contracts endpoint lets you test the mapping logic without any payment setup.

curl -X POST https://cf-worker.selbyventurecap.workers.dev/contracts/apollo-to-salesforce-lead-v1 \
  -H "Content-Type: application/json" \
  -d '{"first_name":"Jane","last_name":"Doe","cell":"4155551234","company":"Acme"}'