"EU-Verify Identity or Document Verification Service" matching MCP servers:

Browser acceptance testing for AI agent deliverables: verify agent output in real Chromium from JSON specs, with MCP server, visual regression, multi-browser support and GitHub Actions.

A verification infrastructure and MCP server that specializes in refutation (negation) rather than generation, providing tools for counterexample search, Lean verification, and audit chains with a 4-value verdict system.

An MCP server that performs independent verification of artifacts against criteria using a different AI model lineage (codex, OpenAI, or Gemini) to catch defects that same-family checks might miss.

Compares weekly work reports against original data to identify incorrect values, missing items, and narrative inconsistencies, providing verification results to users.

MCP server that gives an AI agent a throwaway test identity — a real disposable email address and a real UK phone number — so it can sign up for something it's testing and read back the verification email/SMS itself, without a human in the loop.

Enables AI agents to formally verify constant-time, masking, and patch completeness properties of Verilog hardware designs, providing concrete leakage signals and next-step guidance.

An MCP server for validating AI-generated code through automated browser testing, evidence collection, and intelligent diagnostics.

Provides a deterministic pre-install security scan for Agent skills, plugins, and MCP servers via stdio, returning verdicts, audited badges, CI gates, and reports without executing code or making network calls.

An MCP server for verifying AI-generated code quality, security, and performance, addressing trust gaps in AI coding assistants.

Enables agents to classify every claim into evidence tiers (FACT/INFERENCE/SPECULATION/UNVERIFIED) with attached evidence, forcing deterministic, evidence-gated reporting without LLM or network calls.

Enforces that tasks are created with criteria, claimed by one agent with evidence, and verified by a different agent, preventing self-verification and ensuring independent validation.

This MCP server enables managing CI patch verification workflows by creating, running, tracing, previewing, and canceling patch verification tasks through local stdio tools.

MCP server for Jama Connect that brings requirements, traceability, tests, and baselines into MCP clients like Claude, Cursor, VS Code, or GitHub Copilot, with access control, audit trail, and rate limiting. It provides 53 tools across 8 individually enableable toolsets, with an admin dashboard for managing access and usage.

Enables automated WCAG 2.2 AA accessibility audits of Figma designs and webpages. Generates detailed markdown reports with severity-grouped violations, specific criterion references, and concrete fix recommendations.

Free VOP (Verified Output Protocol) verification for AI agent outputs — score any output 0-100 and get a PASS/PARTIAL/FAIL verdict. No account, no escrow, no financial transaction of any kind.

Semantix-Verify is an MCP server for semantic validation of AI/LLM outputs. It exposes a single tool, verify_text_intent(text, intent_description, threshold), which uses a local quantized NLI cross-encoder (INT8 ONNX) to return a 0.0–1.0 probability that the text satisfies the given intent — and, when it doesn't, a structured correction prompt for agent retry loops. Useful for building com

Enables interaction with Gremlin's reliability management APIs to monitor service dependencies, run reliability experiments, generate reliability reports, and manage chaos engineering tests through natural language queries.

Enables a stateless, horizontally scaled MCP server using the 2026-07-28 specification, with tools for load testing and instance-aware operations.

Enables AI coding agents to autonomously interact with, test, click inline buttons on, and verify Telegram bots end-to-end via MTProto.

Enables AI-powered document analysis and querying for project documentation using vector embeddings stored in Redis. Supports document upload, context-aware Q\&A, automatic test case generation, and requirements traceability through OpenAI integration.