CRM CSV Preflight (Sales List Rescue)
Detect-only CSV check before CRM import: duplicate, invalid and role emails, blanks, phones, dates.
Should I use this
Quality & Safety
Findings (5)
- HIGHTool poisoning patterns detected
- MEDIUMTool 'preflight_csv' description contains placeholder textin preflight_csv
- MEDIUMTool 'preflight_sample' description contains placeholder textin preflight_sample
- INFOTool description contains placeholder or incomplete textin preflight_csv
- INFOTool description contains placeholder or incomplete textin preflight_sample
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"crm-csv-preflight": {
"url": "https://pureservices.store/mcp"
}
}
}Remote endpoints
https://pureservices.store/mcpstreamable-httpWhat it can do
Tool inventory
Tools (2)
🟢preflight_csv(csv, default_country_code, email_column, phone_column, required_columns)
Checks a contact or lead CSV (passed as text, up to 500 data rows and 64 KiB) before a CRM import and reports what it finds: duplicate emails (matched ignoring case and surrounding spaces), invalid email syntax, role or shared inboxes (info@, sales@ and similar), blank required fields (placeholders like N/A, null and - count as blank), phone numbers not written as + country code and digits only (with a suggested form when the fix is mechanical), country and state spelling drift, mixed or ambiguous date formats, and file problems (garbled characters, ragged rows, formula-like cells, stray spaces, header issues). Detection only: it changes nothing, returns no cleaned file, and does not store or log your CSV. Pattern-based; it does not check that mailboxes exist. Same checks as the free Sales List Rescue CSV preflight checker on pureservices.store.
Input Schema
{
"type": "object",
"properties": {
"csv": {
"type": "string",
"description": "The full CSV text including the header row. Comma, semicolon, tab or pipe delimited (auto-detected)."
},
"default_country_code": {
"type": "string",
"enum": [
"1",
"44",
"61",
"49",
"33",
"91",
""
],
"default": "1",
"description": "Calling code assumed for phone numbers without a + prefix: 1 (US/Canada), 44, 61, 49, 33, 91, or \"\" for no default."
},
"email_column": {
"type": "string",
"description": "Header name of the email column. Optional; auto-detected when omitted."
},
"phone_column": {
"type": "string",
"description": "Header name of the phone column. Optional; auto-detected when omitted."
},
"required_columns": {
"type": "array",
"items": {
"type": "string"
},
"description": "Header names that must not be blank. Optional; defaults to the detected email, first name, last name and company columns."
}
},
"required": [
"csv"
],
"additionalProperties": false
}🟢preflight_sample
Runs the same checks as preflight_csv on the checker's built-in sample CSV (fake placeholder data) and returns the sample plus its report, so you can see the report format without sending a file. Detection only; does not store or log your CSV.
Input Schema
{
"type": "object",
"properties": {},
"additionalProperties": false
}Community
Evidence