"Information about OBS (Open Broadcaster Software)" matching MCP servers:

AI-powered code review tool that detects AI-generated code defects invisible to traditional linters — hallucinated packages, deprecated APIs, cross-file contradictions, hidden security anti-patterns, and over-engineering. Works as a standalone CLI, GitHub Action, or MCP server. Supports TypeScript, Python, Java, Go, and Kotlin. Free for individuals, no API key required.

MCP server for Godot Engine enabling AI to autonomously develop, test, and debug games with deterministic playtesting, multiplayer testing, DAP debugging, LSP integration, and token efficiency.

An MCP server for mobile automation that enables LLMs to interact with Android and iOS devices through screenshot, tap, swipe, log analysis, and app lifecycle management.

Enables reproducible evaluation of AI coding agents by exposing repository inspection, code editing, test running, and deterministic verification through MCP tools.

Enables AI assistants to interact with iOS Simulators and Android Emulators, allowing autonomous app development, UI interaction, profiling, and debugging through natural language.

Gives AI assistants a fully offline toolchain for FlyThings OS human-machine interface development: converting HTML prototypes into JSON/FTU layouts, packaging and deploying firmware to devices, capturing real-device screenshots for pixel-diff acceptance, and generating i18n, tests, and bug reports. It also bundles a local vector-plus-BM25 knowledge base covering hardware models, UI control semantics, dependency manifests, and reusable components.

Gives your AI the super power of traveling back in time to find what went wrong and fix the bug timeline.

An MCP server for Unity that provides 300 typed tools for editor automation, asset analysis, validation, and diagnostics, supporting live Editor, headless batch, and offline modes.

Checks the outcome after an agent handoff, when a request, 200 or ack only shows the handoff. Reads one field of one exact public HTTPS JSON record, with a same-site known-good control, for 20-120 s. Returns PROVED, DISPROVED or INCONCLUSIVE with a signed receipt you can verify. 5 free checks, then USD 1 per completed check, by card (Stripe Checkout) or existing Link wallet. INCONCLUSIVE is free.

Enables AI coding assistants to scan an iOS, Android, Flutter, React Native or Expo project for App Store and Google Play rejection risks, returning deterministic findings that cite the guideline section, link to the official Apple or Google page and explain how to fix each problem. Nothing leaves the machine and no AI is used in the checks.

Lets any MCP client, such as Claude, browse attack suites and probes, run a full assurance assessment with all reports written out, send custom prompts or multi-turn histories and get leak, PII and refusal checks back for adaptive attacks, and read findings from an earlier assessment. This enables agent-driven red-teaming of a chatbot, RAG app or AI agent without leaving the chat client.

Enables recurring website maintenance checks — domain registration, SSL certificates, uptime, technical SEO and accessibility — across a portfolio of client sites, using publicly available information. Results are returned as structured data and can be sorted by urgency into a client-ready report.

Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.

Provides an isolated workspace for testing candidate code, runs tests, and returns deterministic pass/fail verdicts. Enables automated grading of software engineering solutions by ensuring reproducible test runs.

Open-source verification for evidence-grounded AI. Runs deterministic grounding checks of AI outputs against source evidence, with no LLM judge.

Open behavioral litmus for MCP servers — grades A–F across tool-output injection, egress, sensitive-data, and adversarial-input, with reproducible, content-addressed evidence. Tools: run_litmus, verify_attestation.

Scans any website and produces an Agent Readiness Report scored on the open ASO framework.

An MCP server that gives AI assistants the ability to check open-source packages for vulnerabilities, enrich findings with real-world exploit intelligence, and statically analyse whether vulnerable code is actually reachable in your project.

Enables AI agents to perform software engineering tasks inside an isolated, deterministic sandbox—exploring repositories, reproducing failures, applying patches, running tests, and verifying solutions against hidden suites through MCP tools.

An intelligent MCP toolset for software testers that monitors code changes, analyzes test impact, recommends tests, and assesses risk, supporting multiple AI coding frameworks via dual transport modes.