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MCP Fathom Analytics

Name: MCP Fathom Analytics
Author: mackenly

by mackenly

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

MCP Fathom 분석

AI 어시스턴트를 통해 Fathom Analytics 데이터에 액세스하기 위한 비공식 모델 컨텍스트 프로토콜( MCP ) 서버입니다. 이 구현은 Fathom Analytics API와 상호 작용하기 위해 @mackenly/fathom-api 비공식 SDK를 사용합니다. Fathom Analytics와 제휴, 보증 또는 지원되지 않습니다. npx 스크립트로 npm 에 게시됩니다.

특징

MCP 서버는 다음과 같은 Fathom Analytics 도구를 제공합니다.

계정 정보

get-account : Fathom Analytics 계정에 대한 세부 정보를 검색합니다.

사이트 관리

list-sites : 모든 Fathom Analytics 사이트를 나열합니다.

이벤트

list-events : 특정 사이트의 이벤트 목록

해석학

get-aggregation : 유연한 필터링 및 그룹화 옵션을 사용하여 집계된 분석 보고서를 생성합니다.

방문자 추적

get-current-visitors : 현재 사이트 방문자에 대한 실시간 데이터를 가져옵니다.

Related MCP server: mcp-site-analyst

용법

Claude Desktop을 사용하는 경우 JSON 구성을 사용하여 MCP 서버를 추가할 수 있습니다( 자세한 내용은 여기를 참조하세요 ). 다음은 예시입니다.

지엑스피1

다른 MCP 클라이언트에 대한 자세한 내용은 여기에서 확인할 수 있습니다. 모델 컨텍스트 프로토콜 예제 클라이언트

API 구조

MCP 서버는 @mackenly/fathom-api SDK를 사용하여 Fathom Analytics API 엔드포인트와 인터페이스합니다.

계정 API : https://api.usefathom.com/v1/account
사이트 API : https://api.usefathom.com/v1/sites
이벤트 API : https://api.usefathom.com/v1/sites/SITE_ID/events
집계 API : https://api.usefathom.com/v1/aggregations
현재 방문자 API : https://api.usefathom.com/v1/current_visitors

집계 예제

집계 도구는 매우 유연합니다. 다음은 몇 가지 사용 사례입니다.

지난 30일간의 일일 페이지뷰 통계 :

{
  "entity": "pageview",
  "entity_id": "SITE_ID",
  "aggregates": "pageviews,uniques,visits",
  "date_grouping": "day",
  "date_from": "2023-08-01 00:00:00"
}

개별 페이지의 성능 :

{
  "entity": "pageview",
  "entity_id": "SITE_ID",
  "aggregates": "pageviews,uniques,avg_duration",
  "field_grouping": "pathname",
  "sort_by": "pageviews:desc",
  "limit": 10
}

특정 국가의 트래픽 :

{
  "entity": "pageview",
  "entity_id": "SITE_ID",
  "aggregates": "visits",
  "field_grouping": "country_code",
  "sort_by": "visits:desc"
}

기여하다

기여를 환영합니다! 풀 리퀘스트를 제출해 주세요.

특허

이 프로젝트는 MIT 라이선스에 따라 라이선스가 부여되었습니다. 자세한 내용은 라이선스 파일을 참조하세요.

Available Tools

5 tools

get-accountB

Get Fathom Analytics account information

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

B3.2/5.0

Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states it 'gets' information, implying a read-only operation, but doesn't specify authentication requirements, rate limits, error conditions, or what 'account information' includes. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with every word contributing to understanding. No waste or redundancy is present.

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

Completeness3/5

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

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate but incomplete. It specifies what is retrieved ('account information') but not the format or scope of the return data. For a read operation with no structured output documentation, more detail on the response would be helpful.

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 has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description adds no parameter information, which is appropriate here. Baseline is 4 for zero parameters, as no compensation is needed for schema gaps.

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 clearly states the verb ('Get') and resource ('Fathom Analytics account information'), making the purpose understandable. It doesn't explicitly differentiate from sibling tools like 'get-aggregation' or 'list-sites', but the specificity of 'account information' provides some implicit distinction. This is clear but lacks explicit sibling differentiation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'get-aggregation' or 'list-sites'. It doesn't mention prerequisites, context, or exclusions. Without any usage instructions, the agent must infer based on tool names alone, which is insufficient for optimal selection.

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

get-aggregationC

Get aggregated analytics data from Fathom

ParametersJSON Schema

Name	Required	Description
`entity`	Yes	The entity to aggregate (pageview or event)
`entity_id`	Yes	ID of the entity (site ID or event ID)
`aggregates`	Yes	Comma-separated list of aggregates to include (visits,uniques,pageviews,avg_duration,bounce_rate,conversions,unique_conversions,value)
`date_grouping`	No	Optional date grouping
`field_grouping`	No	Comma-separated fields to group by (e.g., hostname,pathname)
`sort_by`	No	Field to sort by (e.g., pageviews:desc)
`timezone`	No	Timezone for date calculations (default: UTC)
`date_from`	Yes	Start date (e.g., 2025-01-01 00:00:00 or 2025-01-01)
`date_to`	Yes	End date (e.g., 2025-12-31 23:59:59 or 2025-12-31)
`limit`	No	Limit on number of results
`filters`	No	Array of filter objects

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'gets' data, implying a read-only operation, but doesn't mention any behavioral traits such as rate limits, authentication requirements, data freshness, or potential side effects. For a tool with 11 parameters and no annotation coverage, this is a significant gap.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the tool's complexity (11 parameters, no output schema, and no annotations), the description is insufficient. It doesn't explain what the aggregated data looks like, how results are formatted, or any constraints on usage. For a data retrieval tool with many parameters, more context is needed to guide effective use.

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?

The schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds no additional meaning or context beyond what's already in the schema, such as explaining relationships between parameters or providing usage examples. This meets the baseline for high schema coverage.

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 clearly states the action ('Get aggregated analytics data') and the source ('from Fathom'), which is specific and unambiguous. However, it doesn't differentiate this tool from its siblings (like 'list-events' or 'list-sites'), which might also retrieve analytics data, so it doesn't reach the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'list-events' or 'list-sites'. It lacks explicit instructions on context, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name and parameters alone.

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

get-current-visitorsC

Get current visitors for a Fathom Analytics site

ParametersJSON Schema

Name	Required	Description	Default
`site_id`	Yes	ID of the site to retrieve current visitors for
`detailed`	No	Whether to include detailed content and referrer information

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves current visitors but doesn't explain what 'current' means (e.g., real-time, last hour), whether it's a read-only operation, if there are rate limits, or what the output format looks like. This leaves significant gaps for a tool that likely involves data retrieval.

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 a single, direct sentence that efficiently conveys the core purpose without any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the complexity of retrieving analytics data, no annotations, and no output schema, the description is insufficient. It doesn't cover behavioral aspects like data freshness, permissions, or response structure, leaving the agent with incomplete information to use the tool effectively in context with its siblings.

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?

The input schema has 100% description coverage, clearly documenting both parameters. The description adds no additional semantic context beyond what's in the schema (e.g., it doesn't clarify what 'detailed' information includes or provide examples). This meets the baseline for high schema coverage but doesn't enhance understanding.

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 clearly states the action ('Get') and resource ('current visitors for a Fathom Analytics site'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list-events' or 'get-aggregation' which might also retrieve visitor-related data, so it doesn't reach the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or compare it to siblings like 'list-events' for historical data or 'get-aggregation' for summarized metrics, leaving the agent with no contextual usage information.

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

list-eventsB

List all events for a Fathom Analytics site (automatically handles pagination)

ParametersJSON Schema

Name	Required	Description	Default
`site_id`	Yes	ID of the site to retrieve events for
`limit`	No	Optional limit on the number of events to return

TDQS

B3.3/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context by mentioning automatic pagination handling, which is a key behavioral trait beyond the basic 'list' function. However, it doesn't cover other aspects like rate limits, authentication needs, or error handling, leaving gaps in transparency.

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 a single, efficient sentence that front-loads the core action ('List all events') and adds valuable behavioral context ('automatically handles pagination') without any wasted words. Every part earns its place, making it highly concise and well-structured.

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

Completeness3/5

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the main action and pagination behavior, but lacks details on return values, error cases, or integration with sibling tools, leaving room for improvement in context.

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?

The input schema has 100% description coverage, so the schema already documents both parameters ('site_id' and 'limit') fully. The description implies filtering by site but doesn't add syntax or format details beyond what the schema provides, aligning with the baseline score when schema coverage is high.

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 clearly states the verb ('List') and resource ('events for a Fathom Analytics site'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'get-aggregation' or 'get-current-visitors', which might also retrieve event-related data, so it doesn't reach the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, such as 'get-aggregation' for summarized data or 'get-current-visitors' for real-time events. It lacks explicit when/when-not statements or named alternatives, offering only basic context without exclusions.

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

list-sitesC

List all Fathom Analytics sites on the account

ParametersJSON Schema

Name	Required	Description	Default
`limit`	No	Optional limit on the number of sites to return

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states the action ('List all...') but doesn't disclose behavioral traits like pagination, rate limits, authentication requirements, or what happens if no sites exist. For a list operation with zero annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence that directly states the tool's purpose with zero wasted words. It is appropriately sized and front-loaded, making it easy to parse quickly.

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

Completeness2/5

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

Given the complexity of a list operation with no annotations and no output schema, the description is incomplete. It lacks details on return values, error handling, or behavioral constraints, which are crucial for an agent to use the tool effectively in this context.

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?

The schema description coverage is 100%, with the single parameter 'limit' fully documented in the schema. The description adds no additional meaning about parameters, such as default behavior or format details, so it meets the baseline for high schema coverage without compensating value.

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 clearly states the verb ('List') and resource ('all Fathom Analytics sites on the account'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get-account' or 'get-aggregation', which might also retrieve account-related data, so it misses full sibling distinction.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'get-account' or 'list-events'. It lacks context on prerequisites, such as authentication needs, or exclusions, leaving the agent with minimal usage direction.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

5 tool updatesv1.0.0Jan 2, 2026
- First observedget-account
- First observedget-aggregation
- First observedget-current-visitors
- First observedlist-events
- First observedlist-sites

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.5/5.0

Scored 2026-04-18 11:35 across 5 tools

Disambiguation5/5

Each tool has a clearly distinct purpose targeting different resources: account info, aggregated data, current visitors, events, and sites. There is no overlap in functionality, making it easy for an agent to select the right tool without confusion.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using hyphen-separated lowercase words (e.g., get-account, list-sites). The naming is predictable and uniform across all tools, enhancing readability and usability.

Tool Count5/5

With 5 tools, the server is well-scoped for analytics purposes, covering key operations like retrieving account details, aggregated data, real-time visitors, events, and sites. Each tool earns its place without being overly sparse or bloated.

Completeness4/5

The tool set provides comprehensive read-only coverage for analytics data, including account, sites, events, and current visitors. A minor gap exists in write operations (e.g., creating or updating sites/events), but agents can still perform most common analytics tasks effectively.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

Need Help?

Reddit Discussion

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MCP Fathom 분석

특징

계정 정보

사이트 관리

이벤트

해석학

방문자 추적

용법

API 구조

집계 예제

기여하다

특허

Available Tools

Tool Schema Changelog

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

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