@lodd/mcp-server

get_bot_report

Retrieve a report of bot and crawler traffic filtered from your analytics, grouped by user agent with session counts, page views, and first/last seen dates. Identify AI crawlers, search engines, and SEO tools visiting your site.

Instructions

Show bot and crawler traffic that's been filtered from analytics. Groups by user agent, showing sessions, page views, countries, and first/last seen. Useful for understanding what's crawling your site (AI crawlers, search engines, SEO tools).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "site": "<site>"
    },
    "name": "get_bot_report"
  }
}

Input Schema

Name	Required	Description	Default
`site`	Yes	Site domain or UUID
`limit`	No	Max results (1-1000)
`period`	No	Time period	30d

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.15Jul 28, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description bears full responsibility for behavioral disclosure. It describes grouping and data fields but does not disclose whether the tool is read-only, any authorization requirements, rate limits, or what happens when no bot traffic exists. The implication is that it's a read-only report, but not stated explicitly.

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?

The description is two sentences with no wasted words. The first sentence front-loads the verb and resource, and every sentence adds distinct value: purpose, grouping, and use case.

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?

The description adequately covers the tool's purpose and output fields. However, without an output schema, it would benefit from a brief mention of the response format (e.g., 'Returns a list of user agents with metrics'). For a simple reporting tool, this is a minor gap.

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 fully documents the three parameters. The description adds context about the data fields (countries, first/last seen) but does not add new parameter semantics beyond what the schema already provides. Baseline 3 is appropriate.

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?

The description uses a specific verb ('Show') and resource ('bot and crawler traffic'), clearly distinguishing this tool from siblings like get_analytics or get_traffic_sources. It explicitly states the grouping and data fields, leaving no ambiguity about what the tool does.

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?

The description provides clear context ('Useful for understanding what's crawling your site'), but does not explicitly state when not to use this tool or mention alternatives among the many analytics siblings. A brief note on when to prefer get_analytics or get_traffic_sources would strengthen this.

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