"A tool for developing applications with Xcode" matching MCP servers:

MCP server that helps AI agents inspect Minecraft project evidence (crash logs, mod files, datapacks) before writing development code.

Bridges AI assistants with Xcode to control projects, builds, simulators, testing, and debugging without manual interaction.

MCP server for Xcode build optimization, providing build-timing analysis, DerivedData/module-cache management, and build-speed config linting for AI coding agents.

Gives Goose/Cursor access to your iOS/macOS project index through the Model Control Protocol (MCP) and IndexStoreDB. This provides exhaustive lists of function call sites to help your agent with refactoring and code navigation.

Bridges Xcode and Cursor to provide real-time access to build errors, warnings, and debug output from Xcode's DerivedData, enabling automated error analysis and fixes directly within Cursor.

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.

Connects to Xcode's build system to extract, parse, and display errors and warnings from your Swift projects, helping AI assistants quickly identify code issues without manually searching through build logs.

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.

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.

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.

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 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.

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

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.

Provides code generation and completion capabilities using the DeepSeek API, with support for tool chaining and cost optimization.