Microsoft Clarity MCP

io.github.surendranb由 GitHub 帳號 surendranb 發布v0.1.3更新於 Nov 3, 2026

Microsoft Clarity MCP: behavioral UX analytics, rage clicks, dead clicks, scroll, and JS errors.

發布方自己的服務：Microsoft Learn MCP

已驗證STDIO僅桌面開發者工具資料與分析

服務詳細資訊

識別碼: io.github.surendranb/microsoft-clarity-mcp
傳輸: STDIO
執行環境: Desktop only
信任: Verified
發布於: Oct 29, 2026

安全提示

MCP 服務會接收對話中的工具呼叫請求，並可能執行外部操作。啟用前請先了解該服務能做什麼，並只授予它所需的權限。

註冊中心已驗證此條目所屬的 GitHub 帳號 surendranb。這並不表明該帳號就是產品方。

SourceWeft 的檢查只涵蓋條目是否完整、端點是否回應；不審查伺服器的程式碼，也不審查其工具的行為。

在 README 中新增徽章

向讀者展示該 MCP 服務已收錄於 SourceWeft，徽章連結到本頁。

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/io.github.surendranb%2Fmicrosoft-clarity-mcp.svg)](https://sourceweft.com/mcp/io.github.surendranb%2Fmicrosoft-clarity-mcp?utm_source=readme&utm_medium=badge)

概覽

AI 產生的概覽

本機 MCP 伺服器，把 Microsoft Clarity 的行為 UX 資料（暴怒點擊、無效點擊、快速返回、JS 錯誤）提供給 AI 助理分析。

可以做什麼: 取得 Clarity 專案的高階 UX 洞察：工作階段數、挫折率、過度捲動與技術健康狀況
依 URL、裝置、瀏覽器、作業系統或國家/地區拆分挫折指標（暴怒點擊、無效點擊、快速返回）
分析各瀏覽器與作業系統下的 JavaScript 錯誤與未捕捉例外
診斷憑證、專案設定、本機快取與當日剩餘配額
列出並載入內建技能手冊，並檢查 PyPI 上的新版本
適用情境: 適合讓助理根據 Microsoft Clarity 資料排查網頁 UX 摩擦與前端錯誤，例如排序問題頁面或調查 JavaScript 例外，而不必開啟 Clarity 後台。
執行需求: 透過 stdio 在本機執行，以 uvx 或 npx 啟動（需 Python 或 Node.js）。需要 Microsoft Clarity 資料匯出 API 權杖（環境變數 CLARITY_API_TOKEN）與專案 ID（CLARITY_PROJECT_ID），兩者都在 Clarity 專案設定的 Data Export 中產生。需要連線 Clarity API 的網路；僅支援桌面用戶端。

安裝前請注意

需要 Clarity API 權杖，該憑證可存取專案分析資料，請勿寫入共用設定。Clarity 每個專案每天僅允許 10 次請求，因此回應會快取在本機 ~/.clarity_mcp/cache.json，配額用盡時可能回傳附警告的過期資料。此套件預設傳送匿名使用遙測，可透過 DO_NOT_TRACK、DISABLE_TELEMETRY 或 CLARITY_TELEMETRY 關閉。

安裝

在 SourceWeft 中

開啟儀表板中的 Microsoft Clarity MCP，將其新增到工作區。
為需要使用其工具的對話啟用該服務。

Desktop only，透過 STDIO。 STDIO 服務會啟動本機處理程序，因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照儲存庫中的啟動說明。

README

Microsoft Clarity MCP Server (`microsoft-clarity-mcp`)

FastMCP server exposing Microsoft Clarity's Data Export API for behavioral UX analysis, rage clicks, dead clicks, quick backs, excessive scrolling, and JavaScript runtime errors.

Companion behavioral diagnostics engine to Google Analytics and Search Console for AI agents.

1. Quickstart

Run directly without installing via uvx (Python) or npx (Node):

Via Python (`uvx`)

Via Node (`npx`)

2. MCP Client Configuration

Add to your MCP client config (claude_desktop_config.json, cursor.json, or Antigravity/OpenCode):

json

{  "mcpServers": {    "microsoft-clarity": {      "command": "uvx",      "args": ["microsoft-clarity-mcp"],      "env": {        "CLARITY_API_TOKEN": "your_clarity_api_token_here"      }    }  }}

{  "mcpServers": {    "microsoft-clarity": {      "command": "uvx",      "args": ["microsoft-clarity-mcp"],      "env": {        "CLARITY_API_TOKEN": "your_clarity_api_token_here"      }    }  }}

Or using npx:

json

{  "mcpServers": {    "microsoft-clarity": {      "command": "npx",      "args": ["-y", "microsoft-clarity-mcp"],      "env": {        "CLARITY_API_TOKEN": "your_clarity_api_token_here"      }    }  }}

{  "mcpServers": {    "microsoft-clarity": {      "command": "npx",      "args": ["-y", "microsoft-clarity-mcp"],      "env": {        "CLARITY_API_TOKEN": "your_clarity_api_token_here"      }    }  }}

3. Authentication & API Tokens

Microsoft Clarity secures data export via static JWT Bearer tokens:

Log in to Microsoft Clarity.
Open your project dashboard.
Navigate to Settings -> Data Export.
Click Generate new API token (provide a name between 4 and 32 alphanumeric characters, e.g. clarity-agent).
Copy the generated token and configure CLARITY_API_TOKEN.

4. Rate-Limit Defense & Persistent Caching

Daily Quota: Microsoft Clarity strictly allows 10 requests per project per day.
Automatic Cache: To safeguard user quota from runaway agent loops, all responses are cached locally on disk at ~/.clarity_mcp/cache.json with a 1-hour TTL (configurable via CLARITY_CACHE_TTL).
Stale Cache Fallback: If the daily 10-request quota is reached, the server automatically serves stale cached data with an explicit warning, ensuring your agents remain operational without hard crashing.
Quota Transparency: Every tool response includes metadata detailing calls_used_today, remaining_today, and daily_limit.

5. Tools

Tool	Parameters	Description
`get_ux_insights`	`project_id`, `num_of_days=3`, `token`	High-level behavioral friction metrics: session counts, rage clicks, dead clicks, quick backs, excessive scroll, and JS errors.
`get_frustration_breakdown`	`project_id`, `dimension="URL"`, `num_of_days=3`, `token`	Ranks friction severity broken down across URL paths, devices, browsers, operating systems, or countries.
`get_js_errors`	`project_id`, `num_of_days=3`, `token`	JavaScript runtime exceptions and error clicks grouped across browsers and operating systems.
`doctor`	`project_id`, `token`	Diagnostic utility checking token format, cache integrity, and remaining daily API quotas.
`skills_list`	(none)	Lists dynamic skill playbooks bundled with the server.
`skill_read`	`name`	Fetches operational playbooks (e.g. `ux-triage`, `setup-clarity-token`, `frustration-audit`).
`check_for_updates`	(none)	Queries PyPI for newer versions and upgrade commands.

6. Telemetry & Privacy

This package includes anonymous usage telemetry to ensure reliability and detect runtime bugs across different client harnesses. Telemetry adheres strictly to Schema v2:

Opt-Out: Strictly respects DO_NOT_TRACK=1, DISABLE_TELEMETRY=1, or CLARITY_TELEMETRY=false.
Zero PII: No user URLs, personal identifiers, or authentication tokens are ever captured.

License

來源：README.md，提交 4b5e001

工具

get_ux_insights

Retrieve high-level UX insights, frustration rates, and technical health for a Clarity project. Args: project_id: Microsoft Clarity Project ID (e.g., 'yz5idaioq2'). num_of_days: Lookback window in days (1, 2, or 3 days; defaults to 3). token: Optional Clarity API token. If omitted, uses CLARITY_API_TOKEN environment variable. Returns: Structured JSON summary of session overview, rage clicks, dead clicks, quick backs, excessive scrolling, JS errors, and quota status.

輸入參數tokenproject_id必填num_of_days

get_frustration_breakdown

Break down user frustration metrics (rage clicks, dead clicks, quick backs) across a specific dimension. Args: project_id: Microsoft Clarity Project ID. dimension: Breakdown dimension: 'URL', 'Device', 'Browser', 'OS', or 'Country/Region'. Defaults to 'URL'. num_of_days: Lookback window in days (1, 2, or 3; defaults to 3). token: Optional Clarity API token. Returns: Structured JSON ranking dimension values by user frustration severity.

輸入參數tokendimensionproject_id必填num_of_days

get_js_errors

Analyze JavaScript errors and unhandled exceptions across browsers and operating systems. Args: project_id: Microsoft Clarity Project ID. num_of_days: Lookback window in days (1, 2, or 3; defaults to 3). token: Optional Clarity API token. Returns: Structured JSON breakdown of JavaScript script errors and error clicks by Browser and OS.

輸入參數tokenproject_id必填num_of_days

doctor

Validate Microsoft Clarity credentials, project configurations, on-disk cache, and remaining daily request quota.

輸入參數tokenproject_id

skills_list

List available dynamic skill playbooks bundled with microsoft-clarity-mcp.

無需輸入參數。

skill_read

Load a dynamic skill playbook by name from GitHub (with local fallback). Args: name: Skill name (e.g., 'ux-triage', 'setup-clarity-token', 'frustration-audit').

輸入參數name必填