"ROS" matching MCP servers:

Provides static analysis of ROS 2 workspaces, enabling inspection of packages, dependencies, interfaces, launch files, and robot descriptions without running ROS 2.

Provides ROS2 workspace graph knowledge including package dependencies, message/service/action definitions, and topic pub/sub relationships through MCP tools.

AIContextBuilder (AICB): Roslyn MCP server for C#/.NET code intelligence. Gives coding agents semantic code analysis and navigation instead of text search: callers, change impact, implementations, dependency injection, covering tests, side effects, dead code and token-budgeted context. Installs as a dotnet tool and analyzes any csharp solution locally.

Roslyn-based MCP server providing semantic code intelligence for .NET codebases — type hierarchies, call sites, DI registrations, and reflection usage for Claude Code

Enables source-first orchestration and knowledge indexing with inspectable architectural capabilities through a unified MCP interface, including named-attribute retrieval and atomic knowledge ingestion.

Provides Roslyn-based code intelligence for AI coding agents via MCP, enabling efficient navigation and surgical edits of C# solutions.

Provides C# coding agents with compiler-accurate symbol analysis, including references, renames, and impact analysis for .NET solutions.

Local-first MCP server for semantic C# analysis, navigation, validation, and refactoring using Roslyn on real .NET workspaces.

Enables Codex to access C# diagnostics, navigation, and refactorings through the official Roslyn language server, including definitions, implementations, references, renames, fixes, and refactorings.

A single MCP server that bridges to any LSP, enabling code intelligence features like hover, go-to-definition, references, and diagnostics for multiple languages via configurable language servers.

Enables local semantic code search across repositories using natural language, with AST-aware chunking and hybrid vector/FTS5 retrieval.

Checks cross-branch compatibility for merge conflicts by detecting function signature changes, route conflicts, and schema mismatches across 15+ languages using AST analysis.

Enables AI assistants to diagnose and fix iOS app issues that cause App Store rejections, such as missing privacy manifests, permission strings, and test credentials, before submission.

Enables AI coding agents to review Swift code, scaffold new iOS apps, and build, test, and preview them in the Xcode Simulator using local Apple guides and source references.

Enables AI coding agents to reverse engineer an operating system from its ISO and rebuild it component by component, exposing 39 tools over stdio for ISO fingerprinting, sandboxed QEMU VM lifecycle, PE analysis, API-surface dumps, syscall tracing, behavior diffs, component scaffolding, compat shims, app-compat testing, and knowledge-base search. It lets an agent survey a reference OS, generate clean-room specs and code, boot the rebuild, and test real applications against it.

MCP server for iOS reverse engineering, enabling static analysis of IPA/Mach-O binaries and dynamic instrumentation via Frida for tasks like IAP interception and FairPlay decryption.

Analyzes scroll-triggered animations on any webpage using Playwright, extracting GSAP, ScrollTrigger, Lenis, and CSS code via AST and runtime detection.

MCP Blast-Radius Auditor — statically extract what an MCP server can touch and detect declaration divergences against manifest.json. Stdio MCP (mcp-blast-radius) plus CI gate (mcp-blast-radius-gate). pip install mcp-blast-radius==0.2.0

Serves committed .context/ project memory over MCP stdio, letting agents query a codebase's architecture, decisions, constraints, and import graph to find which files a task touches, what depends on them, which tests cover them, and why the code is shaped that way. It also lets agents record decisions and annotate modules so later sessions inherit that knowledge, across one project or several in workspace mode.

Serves an AI coding agent a searchable index of a codebase's existing capabilities and past incidents, so it can find and reuse what already exists before writing new code. Also exposes blast-radius analysis for shared code and lets the agent reindex the knowledge base, all via local retrieval with no model calls or API keys.