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Method CRM MCP Server and API by Cotlet

Convert lead to customer in Method CRM

method_crm_convert_lead_to_customer
Read-onlyIdempotent

Convert lead to customer in the user's own Method CRM account from ChatGPT, Claude or any AI agent. Returns how to do it in Method CRM step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Method CRM Cloud Browser. Method CRM's official API: Method CRM has a full REST API with read and write access to permitted records, but no ready-made official MCP server (checked 23 Oct 2026).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "method_crm_convert_lead_to_customer"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false; the description adds genuinely new context by stating it "opens nothing by itself" and that the actual mutation happens through separate browser tools. The closing note about Method CRM's REST API and lack of an official MCP server adds provenance but little behavioral value for calling the tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first two sentences are front-loaded and earn their place, establishing purpose and the follow-up browser workflow. The third sentence about Method CRM's REST API and the absence of an official MCP server (with a checked date) is extraneous to the agent's decision and dilutes an otherwise tight definition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the return-value burden and does so adequately by saying it returns step-by-step instructions covering screens, buttons and fields. Together with the pointer to the cotlet_browser_* execution path, an agent knows what it gets and what to do next.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is no parameter semantics to compensate for; the baseline for a no-param tool applies. The description correctly implies there is nothing to supply beyond the account context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource ("Convert lead to customer in ... Method CRM") and, crucially, clarifies that the tool returns a step-by-step guide rather than performing the conversion. That distinguishes it from siblings like method_crm_convert_estimate_to_invoice by resource, though no sibling is named explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear workflow: call this to get the screens/buttons/fields, then execute the conversion with the cotlet_browser_* tools in the Cloud Browser. What's missing is any exclusion or prerequisite guidance (e.g., what state a lead must be in), so the when-not side is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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