CallMCP — Phone Call MCP Server

List Tool Execution Logs

list_tool_execution_logs

Read-onlyIdempotent

List per-call voice-agent tool execution traces — outcome, latency, timeout, and a redacted result preview for each routed tool call. Answers "did this tool call actually work".

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_tool_execution_logs"
  }
}

Input Schema

Name	Required	Description
`to`	No
`from`	No
`limit`	No
`call_id`	No	Call/conversation id filter.
`tool_name`	No	Tool name filter (e.g. send_sms).
`business_id`	No	Business ID (optional only when the token can access exactly one business).
`tool_call_id`	No	Exact tool_call_id filter.
`outcome_status`	No	Outcome envelope status filter (e.g. success, needs_clarification, unavailable, queued, retryable_delay, hard_failure).

Output Schema

Name	Required	Description
`logs`	No
`error`	No	Present when success is false
`success`	Yes	Whether the tool completed successfully
`business_id`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A4/5.0

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, so safety is covered; the description adds real value by disclosing that results are redacted previews and that latency/timeout/outcome are reported per routed call. Remaining gap is no guidance on pagination or result volume (limit caps at 100 in schema).

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, front-loaded with the verb and resource, with the payload enumerated compactly and the diagnostic purpose last. No filler or repetition of the title.

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 return values need not be re-explained, and the description nonetheless names the key fields and the redaction caveat. Missing only operational detail such as default/maximum limit behavior and business-scoping expectations, which keeps it short of full completeness.

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 coverage is 63% and the description mentions none of the eight filters (call_id, tool_name, outcome_status, time window). The inclusion of 'per-call' and 'routed tool call' lightly implies call-scoped filtering, but no format or semantics are added beyond the schema.

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

Purpose5/5

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

States a specific verb and resource ('List per-call voice-agent tool execution traces') plus the exact payload returned (outcome, latency, timeout, redacted result preview), which is distinct from siblings like list_conversations or list_observability_events. The closing question gives an agent an immediate mental model of the data.

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 phrase 'did this tool call actually work' hints at a diagnostic use case, but there is no explicit when-to-use, when-not-to-use, or pointer to an alternative sibling. An agent must infer that this is the per-call diagnostic surface rather than the broader events stream.

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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