"An automation tool for workflows and integrations (n8n software)" matching MCP servers:

Provides software design guidance via MCP, including SOLID principles, design patterns, pattern scaffolding, and heuristic code-smell detection to help review and refactor code.

Enables AI agents to operate the Unreal Editor via MCP: reading, creating, and editing blueprints at the node level, authoring materials and UMG widgets, auditing projects, and verifying runtime behavior in PIE with read-back checks.

Lints n8n workflow exports and returns machine-readable findings with per-rule fixes, helping agents and reviewers catch reliability gaps such as missing error workflows, retries that swallow errors, unauthenticated webhooks, and hardcoded secrets without sending data anywhere.

Enables agents to lint exported n8n workflow JSON for security, structure, reliability, and Code node issues, outline workflow paths and branches, review safe auto-fixes, and triage failed executions through MCP tools.

Statically analyzes exported n8n automation workflows for security issues and returns structured findings.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Enables MCP clients to run read-only static audits on supplied n8n, Dify, Trigger.dev, Activepieces, and OpenAPI exports, and to screen HTTPS URLs for unsafe schemes, returning structured findings and limitations.

Enables coverage-driven test generation for RHDH plugin forests by analyzing git diffs and coverage reports, recommending the cheapest test layer, and emitting actionable test briefs, including Playwright MCP prompts for UI gaps.

A sophisticated server that enables AI assistants to automatically analyze codebases and generate comprehensive, professional documentation.

MCP server for automated code review using AI agents. It analyzes code diffs or file paths for bugs, security issues, and style violations.

Enables AI assistants to leverage Qwen's code analysis capabilities with large context windows, supporting file/directory analysis, sandbox execution, and multiple approval modes for safe code operations.

Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

MCP server that enables AI agents to analyze legacy code, plan and execute software migrations, generate modern source code, and validate production-ready artifacts through a multi-agent pipeline.

An MCP server that wraps Microsoft's FastContext as a read-only repository exploration subagent, enabling coding agents to delegate broad code searches and receive compact file:line citations.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Provides AI agents with ground-truth knowledge of Strapi projects by reading real schema files, enabling accurate queries and safe refactoring operations.

Enables MCP-compatible AI clients to inspect Godot project and editor state, observe opted-in running scenes, manage processes, and apply permission-scoped guarded edits. It starts read-only and exposes additional capabilities only through explicit command-line flags.

Uses Claude as an independent second-model reviewer inside Codex, performing reviews on disposable Git snapshots with structured findings.

CodeGuard MCP is a real-time AI code security scanning tool used to detect vulnerabilities, keys, and compliance issues in AI-generated code, and is suitable for code security reviews in development environments

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.

Enables AI assistants to import binaries into Ghidra, trigger analysis, browse functions, symbols, strings, and imports, and read decompiled C code and disassembly via MCP tools.

Enables binary comparison capabilities by leveraging IDA Pro and BinDiff to analyze similarities and differences between files. Users can perform automated function analysis to identify changed functions and compare original binaries against patched versions.

Enables agents to turn a local code project into Chinese software copyright (R11) application materials: scanning candidate files, estimating page layout, and generating a 60-page source-code PDF plus application form fields, extraction lists, desensitization, and validation reports. Also provides field and environment checks and explains the formatting rules behind each output.

Enables local, deterministic review of GitHub and GitLab pull request diffs for secret leaks, OWASP injection issues, WCAG 2.2 AA/EU EAA accessibility gaps, EU AI Act transparency, and database RLS risks, producing risk scores, merge decisions, committable suggestions, and SARIF exports.

Provides GDB and clangd-based tools for debugging C++ programs, enabling step execution, variable inspection, diagnostics, and combined runtime-static analysis.

Enables agents to govern evolving software by measuring trajectory, drift, invariants, and incidents, and by forking and measuring alternative futures before adoption.

MCP server giving Claude (and any MCP-compatible client) live access to SAP systems via ADT for reading, searching, editing, and activating ABAP objects.

Enables autonomous agents to automatically repair and guard tool-call schemas through deterministic AST analysis and parameter projection validation, ensuring reliable, schema-compliant interactions in MCP-compatible environments.