CallMCP — Phone Call MCP Server

List Leads

list_leads

Read-onlyIdempotent

List leads for the authenticated business, with optional status/source/agent filters. Includes the latest AI lead score when available.

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": "list_leads"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Max results to return (default 50, max 100)
`offset`	No	Zero-based pagination offset (default 0)
`source`	No	Filter by lead source (optional)
`status`	No	Filter by lead status (optional)
`agent_id`	No	Filter by agent ID (optional)

Output Schema

Name	Required	Description
`count`	No
`error`	No	Present when success is false
`leads`	No
`limit`	No
`offset`	No
`filters`	No
`success`	Yes	Whether the tool completed successfully
`has_more`	No
`next_offset`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world behavior, so the description does not need to repeat safety traits. It adds useful context by stating that results are scoped to the authenticated business and that the latest AI lead score is included when available. It does not mention pagination behavior or ordering, but the annotations carry the main behavioral burden.

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

Conciseness5/5

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

Two sentences, zero waste, and the core purpose and scoping are front-loaded. The second sentence adds useful return-value context without bloating the 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?

An output schema exists, so the description need not explain return values, and it appropriately mentions the notable AI lead score field. Annotations cover the safety profile. The only minor gap is that sibling differentiation is not explicit, but the definition is otherwise complete for selecting and invoking the tool.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all five parameters, including limits, offsets, and filter fields. The description names the filter categories but adds no syntax, allowed values, or interaction rules beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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 gives a specific verb and resource ("List leads") and clarifies scope ("for the authenticated business"). It also notes optional filters and that AI lead scores are included, which helps distinguish it from a raw envelope. However, it does not explicitly differentiate this from siblings like get_lead or list_lsa_leads, so an agent must infer the boundary.

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

Usage Guidelines3/5

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

The description implies usage by mentioning optional status/source/agent filters, but it gives no explicit guidance on when to use this tool versus get_lead (single lead) or list_lsa_leads (LSA-specific leads). The context is clear enough for basic selection but not for confident routing among similar siblings.

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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