"GPT-SoVITS MCP (Model Context Protocol) Integration" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Official Mifori Agent Trust Protocol. Performs real-time latency, JSON schema compliance, and synthetic IQ audits on target AI bots using x402 USDC micro-payments on Base network before high-value tool execution.
HefestoAI checks AI-generated code before you ship it.
Simulate cloud infrastructure and estimate cost before deploying or changing infrastructure.
Run, debug, and triage tests from your IDE using natural language, no dashboard switching, no manual data transfers. The TestMu AI (formerly LambdaTest) MCP Server is a single remote server exposing four tool suites: HyperExecute — analyze your project, generate YAML configs and test runner commands, then monitor jobs and sessions. Automation — pull a TestID's details plus command, network, and console logs into one chat for instant root-cause analysis. Includes mobile app upload. SmartUI — explain pixel, layout, DOM, and perceptual changes in a visual regression run, with context-aware React/HTML/CSS fixes. Accessibility — audit any public URL or a local React app against WCAG and get ready-to-apply remediation steps. Connects over https://mcp.lambdatest.com/mcp using OAuth 2.1 — no API keys in your config. One-click install in Cursor; works with Claude, GitHub Copilot, Cline, and any MCP client. Tests execute on the TestMu AI cloud: 3,000+ browsers and 10,000+ real devices.
Load testing and synthetic monitoring platform: test with Playwright, Browser Bot, or Protocol Bots.
Receipts for what your AI coding agent says it verified. Short-lived API checks, keys kept out of the model
Country verification research, integration planning and synthetic tests. No live identity checks.
Agentic code review, no signup to try: reality gates + frontier-model review, with veto.
The world's first named AI prompt quality score. Score, optimize, and compare LLM prompts before they hit any model. Free tier available. Built on PEEM, RAGAS, G-Eval, and MT-Bench frameworks. x402-native on Base.
Observed facts on public MCP servers: protocol checks, tool changes, signed evidence. No verdicts.
Scan pasted Stripe webhook/checkout code for common integration bugs.
Synthetic checks, nightly regression replay and model-drift alerts for AI agents
AI integrity standards, benchmarks, and EU AI Act-aligned Tier 0 model certification
PQS scores any prompt before the model runs. 8 dimensions. 5 frameworks. Pre-flight, not post-hoc.
Unpaid qualification-gated operational_context canary. Staging data. No wallet.
Render pages to images and PDFs, audit websites, explain Peppol rules, run integration test rigs.
Give AI assistants the context behind client website feedback. Read comments, screenshots, replies, element details, and developer briefs; organize priorities, update statuses, and export feedback from authorized projects. Coding agents with repository access can investigate issues and prepare fixes for review. Connect through Streamable HTTP and browser OAuth using a Simple Commenter account.
MCP Spec Compliance MCP — audits any MCP server.json against the official Model Context Protocol
## Skill Catalog The library contains 42 public skills organized by Rails development concern. | Category | Examples | |----------|----------| | Planning | `create-prd`, `generate-tasks`, `plan-tickets` | | Testing | `plan-tests`, `write-tests`, `test-service`, `triage-bug` | | Code quality | `code-review`, `respond-to-review`, `security-check`, `refactor-code` | | Architecture and DDD | `define-domain-language`, `review-domain-boundaries`, `model-domain`, `review-architecture` | | Rails imple
Run AI agent evaluations on your own model keys, and publish runs others can review and re-run.
