"Analyzing Football Strategies, Players, and Matches" matching MCP servers:

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Validates .mcp.json and claude_desktop_config files to catch duplicate server names, missing binaries, invalid environment variables, and unreachable endpoints. Reports each problem along with how to fix it, so silently failing MCP servers can be diagnosed and repaired.

Enables users to run synthetic support-agent evaluations, preserve and inspect traces, score results deterministically, inject failures, and enforce release review gates through MCP tools, resources, and prompts.

Windows桌面截图与窗口自动化工具，支持后台操作、不抢焦点，可截取窗口/屏幕、模拟鼠标键盘、点击菜单等。

Provides a framework for running multiple MCP servers using FastAPI, stdio, and streamable-http transports, with an echo tool for testing and integration with MCP Inspector.

Maps Electron app IPC handlers to MCP tools and provides 33 built-in CDP tools for DOM automation, screenshots, interaction, and debugging, enabling Claude Code to directly control your Electron app.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Enables coding agents to identify likely runtime failures in JavaScript and TypeScript by ranking risky files, tracing dependencies, analyzing logs, and obtaining independent model reviews with line-level reasons.

Exposes Semgrep as deterministic, rule-matching analysis tools over MCP so a code-review agent can scan only the lines changed in a diff, scan whole files on demand, and check analyzer availability, version, ruleset, and limits. Results are returned as compact per-finding lines with source snippets suitable as comment anchors, along with counts of suppressed out-of-diff matches.

An intelligent debugging assistant that automates the debugging process by analyzing bugs, injecting HTTP-based debug logs into code across multiple environments (browser, Node.js, mobile, etc.), and iteratively fixing issues based on real-time feedback.

Checks that every computed number in a Markdown document still matches the formula that produced it, and repairs it under an explicit write gate — so an agent's correct formula can't ship with a wrong total. Exposes every VisiMark command as a tool (check, explain, eval, infer, format), the authoring discipline as resources, and the orderings an agent gets wrong unsupplied as prompts. Read-only by

This MCP server gives AI coding agents structured, scoped access to GitHub issues, a codebase, its docs, and its test suite, enabling issue triage, code search, test execution, and failure analysis in one workflow. It provides deterministic tools for fetching and analyzing issues, searching code, reading documentation, running tests, and summarizing failures.

Enables local auditing of trading strategies through MCP checkers for point-in-time data provenance, pre-trade order validation, and regime-fragility testing, while deferring promotion verdicts to a hosted service.

Enables LLMs to systematically develop and validate regex patterns by defining test cases with expected matches, testing patterns against them, and iteratively refining until all requirements are satisfied.

Enables natural language interaction with Kitware CDash for browsing dashboards, triaging CI failures, inspecting build errors and test details, and analyzing coverage.

Enables AI agents to fully control Android devices through over 30 tools for app management, UI automation, and vision-based analysis via ADB. It supports multi-device management, action recording, and smart execution strategies ranging from UI hierarchy parsing to coordinate-based interaction.

A Model Context Protocol server that provides programmatic APIs for running mutation tests with mutmut, analyzing results, and improving test coverage in Python projects.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

Provides prompt templates and tools for mobile QA automation, including converting manual tests to Appium scripts, analyzing failures, and standardizing bug reports.