"Assistance with Debugging Frontend Issues Using JavaScript Code" matching MCP servers:

Enables coding agents to develop on one machine and verify results on another, using branch-bound runbooks, isolated checkpoints, and structured receipts to guide repair iterations.

MCP server that provides AI coding assistants with access to call graphs, data flows, and security analysis for multi-file vulnerability detection.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

A local MCP server that indexes codebases into Neo4j and provides tools for code analysis, dependency visualization, and impact assessment.

An MCP server for fast local source code searching using Zoekt, enabling regex and substring queries across indexed directories.

Turns a codebase into a queryable graph with semantic search, call graphs, and control/data flow analysis, served to AI coding agents via the Model Context Protocol.

AI modifies a function but misses 5 callers that also need updating. crag fixes this — it builds precise call graphs via static analysis, so AI knows exactly what's affected before making changes.

RegressGuard is an MCP server that records a known-good baseline and lets AI coding agents detect regressions (broken API contracts, failing tests, schema changes) during their edit loop, allowing them to self-correct before committing.

An MCP server that provides persistent memory for AI agents, enabling context retention across sessions and supporting vibe-loop workflows where agent promises and deliverables are tracked and validated.

Enables reading and searching API documentation from YApi instances, allowing AI models to access interface definitions, project API lists, and search through API endpoints using YApi URLs or project IDs.

A Bitbucket CLI and MCP server written in Go for managing workspaces, repositories, pull requests, pipelines, issues, and source code. Supports stdio and HTTP transport.

A TypeScript server implementing the Model Context Protocol that provides secure code execution in isolated Docker containers, allowing LLM applications to safely run Python, Go, or JavaScript code snippets.

Enables AI assistants to access SAP ADT APIs for reading, writing, debugging, deploying, and testing ABAP code through natural language or DSL automation.

Enables interaction with Bitbucket through the Model Context Protocol, allowing users to manage pull requests, add comments, review code, create tasks, and perform other repository operations using natural language.

MCP server for managing and serving dynamic prompt templates using elegant and powerful text template engine. Create reusable, logic-driven prompts with variables, partials, and conditionals that can be served to any compatible MCP client like Claude Code, Claude Desktop, Gemini CLI, etc.

Connects AI tools to GitHub and local git repositories, enabling natural language management of issues, PRs, code analysis, and workflows.

A self-hosted MCP server that retrieves git-backed engineering experience records (issues, fixes) to inform LLM coding agents, preventing repeated mistakes with a relevance floor.

MCP server for Lightpanda headless browser enabling ultra-fast HTML extraction, markdown conversion, and JavaScript execution with 16x lower memory footprint than Chrome.

iOS Safari debugging via ios-webkit-debug-proxy — MCP server with full WebKit Inspector Protocol support

Wraps OpenAI's Codex CLI as an MCP server, enabling AI clients like KiloCode, Roo Code, and Cline to leverage Codex for code generation, debugging, and analysis through natural language.