"A knowledge base for advanced JavaScript programming" matching MCP servers:

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables AI agents to verify Ceph CLI commands, config parameters, and review test scripts using a pre-generated knowledge base.

Exposes a version-controlled knowledge base as MCP tools so agents can read merged identity/state summaries and next recommended actions at runtime, plus run deterministic schema validation and cross-reference link checks. This lets agents fetch live state and verify integrity via self-describing calls instead of re-reading raw files.

This MCP server builds a local flakiness knowledge graph from Playwright test run history and enables AI agents to query flaky tests, failure patterns, trends, and correlated git commits, helping diagnose test reliability without manual analysis.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

Zero-sidecar MCP server embedded directly in the Godot 4 editor as a GDScript EditorPlugin — no Node or Python sidecar. Reflection-driven tools over any engine class, validate-before-write GDScript, scene/script/resource authoring, and a runtime play-test loop (play, screenshot, input, assert).

Enables LLMs to perform browser automation tasks including web scraping, taking screenshots, and executing JavaScript using Playwright. It facilitates real-time interaction with web pages and the generation of automated test code.

Generates a pytest suite from acceptance criteria that are withheld from the coding agent, so the tests can disagree with the code. Four tools, and qikly_run never returns the criteria, which a test in the suite enforces.

MCP server that brings Trustabl static reliability scanning into Cursor, letting agents inventory agents/tools, flag risky patterns, score production readiness, and write SARIF reports.

Enables AI-powered document analysis and querying for project documentation using vector embeddings stored in Redis. Supports document upload, context-aware Q\&A, automatic test case generation, and requirements traceability through OpenAI integration.

A reference MCP server that enforces identity-aware tool access using role-based permissions (Reader, Analyst, Auditor) and supports multiple identity routes like Entra RBAC, Copilot Studio, and Okta XAA. It provides read-only access to test evidence with explicit denial paths for unauthorized tools.

Zero-dependency MCP server and CLI that proxies, inspects, and analyzes JSON-RPC message streams between MCP clients and servers.

Enables checking npm packages for known security vulnerabilities using the OSV API before installation. Supports both single package checks and bulk vulnerability scanning for multiple packages at once.

A simple server implementing the Model Context Protocol (MCP) that echoes messages back, designed for testing MCP clients.

Bridges AI models with WinDbg to analyze Windows crash dumps and perform remote debugging through natural language queries, enabling execution of debugger commands and automated crash analysis.

A shared, concurrency-safe ledger for LLM code audits. It enables multiple agents to collaboratively report, verify, and resolve bugs with deduplication and hallucination resistance.

Signalint is an MCP server that provides JavaScript and TypeScript diagnostics by running Oxlint, TypeScript, and optionally Biome, with caching, clustering of repeated issues, and detection of oscillating diagnostics.

A Model Context Protocol (MCP) server for debugging and operating Rust Tauri applications over WebSocket.

A deterministic preflight checker for outbound SMS/iMessage that catches silent filtering, segment blowups, and dropped iMessage features before sending.