Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
作者提供的说明(英文原文)
Analyze test coverage from LCOV files - makes AI agents coverage-aware without wasting tokens
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"test-coverage": {
"command": "npx",
"args": [
"-y",
"test-coverage-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add test-coverage -- npx -y test-coverage-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"test-coverage": {
"command": "npx",
"args": [
"-y",
"test-coverage-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"test-coverage": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"test-coverage-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 goldbergyoni 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.1.0)于12个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Agent-Native Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Make your agents coverage-aware as they code for you
“Hey, I’m a coding agent. I just created flashy nifty feature… but oops, I downgraded the coverage 🤓. How could I know that?”
“Hey, I’m a testing agent. I was tasked to cover some code with testing, but how can I find which areas are not covered?😳”
Give your coding and testing agent eyes: MCP server that provides instant, reliable, token-efficient test coverage data for any programming language (LCOV based)
__
🚀 Just launched (November 2025) ! I spend great time these days on polishing this library. If you find this valuable, a ⭐ star helps signal to other developers that this project is worth their attention
When AI coding agents work on your code without proper coverage tooling, they face three critical issues:
This MCP server solves all three problems by providing:
Test Coverage: This project maintains 95% test coverage and we're targeting 100% soon.
Ask for overall project coverage or coverage for specific files:
// Get overall project coverage
coverage_summary({ lcovPath: "./coverage/lcov.info" }); // Returns: { linesCoveragePercentage: 87.5, branchesCoveragePercentage: 82.1 }
// Get coverage for specific files coverage_file_summary({ lcovPath: "./coverage/lcov.info", filePath: "src/utils/parser.ts", }); // Returns: { path: "src/utils/parser.ts", linesCoveragePercentage: 92.0, branchesCoveragePercentage: 88.5 }
Establish a baseline at session start, then measure your progress:
// At session start - record current coverage as baseline
start_recording({ lcovPath: "./coverage/lcov.info" }); // Returns: "Recording started"
// ... agent writes code and tests ...
// Check coverage impact get_diff_since_start({ lcovPath: "./coverage/lcov.info" }); // Returns: { linesPercentageImpact: +2.3, branchesPercentageImpact: +1.8 }
Why baseline tracking? Without it, agents would need to keep initial coverage in their stateful memory throughout the session, consuming valuable context window space.
npm install -g test-coverage-mcp
Add this MCP server to your AI coding tool's configuration:
macOS: Edit ~/Library/Application Support/Claude/claude_desktop_config.json Windows: Edit %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": { "test-coverage": { "command": "npx", "args": ["-y", "test-coverage-mcp"] } } }
After updating, restart Claude Desktop.
Create or edit .cursor/mcp.json in your project root:
{
"mcpServers": { "test-coverage": { "command": "npx", "args": ["-y", "test-coverage-mcp"] } } }
Create or edit .vscode/mcp.json in your workspace:
{
"servers": { "test-coverage": { "command": "npx", "args": ["-y", "test-coverage-mcp"] } } }
Requires VS Code 1.99+ or Visual Studio 17.14+. Enterprise users need "MCP servers in Copilot" policy enabled.
macOS: Edit ~/.codeium/windsurf/mcp_config.json Windows: Edit %APPDATA%\Codeium\Windsurf\mcp_config.json Linux: Edit ~/.codeium/windsurf/mcp_config.json
{
"mcpServers": { "test-coverage": { "command": "npx", "args": ["-y", "test-coverage-mcp"] } } }
Or use the GUI: Settings → Advanced Settings → Cascade → Add Server
coverage_summaryGet overall project coverage from an LCOV file.
Input:
{
lcovPath?: string // Optional. Defaults to "./coverage/lcov.info" }
Output:
{
linesCoveragePercentage: number, // 0-100 branchesCoveragePercentage: number // 0-100 }
Example:
coverage_summary({ lcovPath: "./coverage/lcov.info" });
// { linesCoveragePercentage: 87.5, branchesCoveragePercentage: 82.1 }
coverage_file_summaryGet coverage for a specific file.
Input:
{
lcovPath?: string, // Optional. Defaults to "./coverage/lcov.info" filePath: string // Required. Path to the file }
Output:
{
path: string, linesCoveragePercentage: number, // 0-100 branchesCoveragePercentage: number // 0-100 }
Example:
coverage_file_summary({
lcovPath: "./coverage/lcov.info", filePath: "src/utils/parser.ts", }); // { path: "src/utils/parser.ts", linesCoveragePercentage: 92.0, branchesCoveragePercentage: 88.5 }
start_recordingRecord current coverage as a baseline for later comparison.
Input:
{
lcovPath: string; // Required. Path to LCOV file to record }
Output:
"Recording started";
Example:
start_recording({ lcovPath: "./coverage/lcov.info" });
// "Recording started"
get_diff_since_startCompare current coverage against the recorded baseline.
Input:
{
lcovPath: string; // Required. Path to current LCOV file }
Output:
{
linesPercentageImpact: number, // Positive = improvement, negative = regression branchesPercentageImpact: number // Positive = improvement, negative = regression }
Example:
get_diff_since_start({ lcovPath: "./coverage/lcov.info" });
// { linesPercentageImpact: +2.3, branchesPercentageImpact: +1.8 }
Agent: "Let me check the current test coverage before I start working"
[Uses coverage_summary tool] Agent: "Current coverage is 87.5% lines and 82.1% branches. I'll aim to maintain or improve this."
Agent: "I'll record the baseline coverage first"
[Uses start_recording tool]
Agent: "Now I'll add the new authentication feature with tests" [Writes code and tests]
Agent: "Let me check the coverage impact" [Uses get_diff_since_start tool] Agent: "Great! Coverage increased by 2.3% for lines and 1.8% for branches."
Agent: "Let me check coverage for the file I just modified"
[Uses coverage_file_summary with filePath: "src/auth/validator.ts"] Agent: "The validator.ts file now has 95% line coverage and 92% branch coverage."
This MCP server:
This server supports all standard LCOV file formats, including:
SF:, end_of_record)DA: entries)BRDA:, BRF:, BRH:)./coverage/lcov.infostart_recording before calling get_diff_since_start# Install dependencies
npm install
npm run build
npm test
npm run lint
npm run inspect
Contributions are welcome! Please feel free to submit a Pull Request.
MIT © Yoni Goldberg
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