mcp-server-peecai

URL Citation Report

get_urls_report

Read-onlyIdempotent

Retrieve URL analytics reports including citation counts, retrievals, and citation rates. Filter by date, classification, dimensions, and other criteria to analyze brand visibility in AI-generated answers.

Instructions

Get URL analytics report: citation_count (total citations), retrievals (retrieval count), citation_rate. Classification values: HOMEPAGE, CATEGORY_PAGE, PRODUCT_PAGE, LISTICLE, COMPARISON, PROFILE, ALTERNATIVE, DISCUSSION, HOW_TO_GUIDE, ARTICLE, OTHER. Returns up to limit results (default: 100). Classification is filtered client-side after retrieval. Use filters array for server-side filtering by model, tag, topic, prompt, domain, URL, or country_code. Without date filters, returns data across all available dates. Empty results may indicate the project has no report data for the given time range or filters.

Input Schema

TableJSON Schema

Name	Required	Description
`project_id`	No	Project ID (uses PEECAI_PROJECT_ID env if omitted). Call list_projects to find IDs.
`start_date`	No	Start date (YYYY-MM-DD). Omit for no lower bound.
`end_date`	No	End date (YYYY-MM-DD). Omit for no upper bound.
`dimensions`	No	Breakdown dimensions. Each adds a grouping level to results: prompt_id (by search prompt), model_id (by AI model), model_channel_id (by model channel, e.g. openai-0/perplexity-0), tag_id (by category tag), topic_id (by topic group), date (by date), country_code (by country), chat_id (by individual chat). Multiple dimensions can be combined.
`classification`	No	Filter by URL classification (applied client-side after retrieval).
`filters`	No	Server-side filters. Multiple filters are AND'd together.
`limit`	No	Max results (1-10000, default: 100)
`offset`	No	Results to skip

Tool Definition Quality

A4.6/5.0

Behavior5/5

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

Annotations indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description reinforces this by describing a read operation returning analytics data. It adds transparency about client-side filtering and date range behavior without contradictions.

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

Conciseness4/5

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

The description is a single paragraph that covers all key points. It is not overly verbose, but could be slightly more structured with bullet points for clarity. Nonetheless, every sentence adds value.

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

Completeness5/5

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

With 8 parameters and no output schema, the description comprehensively explains the API behavior: metrics returned, client-side vs server-side filtering, date range effects, default limit, and empty results. It leaves no major gaps.

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?

Schema coverage is 100%, but the description adds value by explaining enum meanings (classification values), dimension effects, and filter behavior. It goes beyond the schema's technical descriptions.

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 clearly states 'Get URL analytics report' and lists the specific metrics (citation_count, retrievals, citation_rate) and classification values. It distinguishes from sibling tools like get_domains_report and get_url_content by focusing on URL-level analytics.

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 guidance on client-side vs server-side filtering via classification and filters arrays, explains date range behavior, and mentions empty results interpretation. However, it doesn't explicitly contrast with alternative report tools like get_brands_report.

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

Install Server

Other Tools

Latest Blog Posts

Lightport: Open-Sourcing Glama's AI Gateway
By punkpeye on April 27, 2026.
open source
OpenAI
Tool Definition Quality Score (TDQS)
By punkpeye on April 3, 2026.
mcp
The Hackers Who Tracked My Sleep Cycle
By punkpeye on March 26, 2026.
security

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/thein-art/mcp-server-peecai'

If you have feedback or need assistance with the MCP directory API, please join our Discord server