Analyze test coverage from LCOV files - makes AI agents coverage-aware without wasting tokens
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Test Coverage MCP.
coverage_summaryGet overall project coverage from an LCOV file.
coverage_file_summaryGet coverage for a specific file.
start_recordingRecord current coverage as a baseline for later comparison.
get_diff_since_startCompare current coverage against the recorded baseline.
Make your agents coverage-aware as they code for you
βHey, Iβm a coding agent. I just created flashy nifty featureβ¦ but oops, I downgraded the coverage π€. How could I know that?β
βHey, Iβm a testing agent. I was tasked to cover some code with testing, but how can I find which areas are not covered?π³β
Give your coding and testing agent eyes: MCP server that provides instant, reliable, token-efficient test coverage data for any programming language (LCOV based)
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π Just launched (November 2025) ! I spend great time these days on polishing this library. If you find this valuable, a β 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:
Establish a baseline at session start, then measure your progress:
Why baseline tracking? Without it, agents would need to keep initial coverage in their stateful memory throughout the session, consuming valuable context window space.
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
After updating, restart Claude Desktop.
Create or edit .cursor/mcp.json in your project root:
Create or edit .vscode/mcp.json in your workspace:
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
Or use the GUI: Settings β Advanced Settings β Cascade β Add Server
coverage_summaryGet overall project coverage from an LCOV file.
Input:
Output:
Example:
coverage_file_summaryGet coverage for a specific file.
Input:
Output:
Example:
start_recordingRecord current coverage as a baseline for later comparison.
Input:
Output:
Example:
get_diff_since_startCompare current coverage against the recorded baseline.
Input:
Output:
Example:
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_startContributions are welcome! Please feel free to submit a Pull Request.
MIT Β© Yoni Goldberg
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