"China Phone Number Risk Control Systems and Fraud Prevention" matching MCP servers:

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Provides secure, controlled access to GitHub operations through the Model Context Protocol with enterprise-grade security features including secret detection, vulnerability scanning, rate limiting, and full audit trails. Supports repository management, file operations, branch creation, commits, and GitHub Actions workflows.

Enables creating release manifests and verifying that local release folders or public HTTPS bytes match the manifest, using read-only MCP tools.

Provides a read-only tool to check Wrangler configuration files for common mistakes before deployment, supporting environment selection and strict mode.

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

A read-only Model Context Protocol server that converts local Git changes and JUnit XML reports into traceable release evidence, risk findings, and a rollback checklist.

Analyzes database migrations for risks like lock contention and data loss before they run. Supports Flyway and Liquibase formats, providing risk scores and rollback generation.

Autonomous coding pipeline exposed as an MCP server: plan, dispatch, review, and merge software stories through worktree-isolated agents. A frontier model (Claude) handles judgment — planning, review, risk adjudication — while a local model does the implementation, gated by TDD and a merge-time test rerun on the rebased branch.

An intelligent MCP server that gives AI agents full control over GitHub Actions CI/CD pipelines, including real-time monitoring, log analysis, AI-powered failure diagnosis, and deployment management.

Enables headless batchmode control of Unity projects for compile, test, build, and screenshot tasks, avoiding the need for an interactive editor.

Provides coding agents and CI with a typed decision layer that sends bounded state and questions to Jev, then returns deterministic actions for review, risk assessment, requirement checks, and verification.

Governance/control plane for MCP-enabled coding-agent workflows with validation, findings, approvals, budgets, and proof bundles.

Deploys projects straight from an AI agent to Snaphost and returns a public URL, with automatic Dockerfile generation, build/run/log management, and deploy lifecycle control.

Enables AI systems like Claude and Cursor to directly manage Railway projects, deployments, services, environment variables, and monitor logs through natural language commands.

Enables monitoring and control of the SST development process by streaming dev logs, managing Lambda invocations, and executing lifecycle commands like start, stop, and restart. It provides real-time access to event streams and deployment status directly through the Model Context Protocol.

Enables AI clients to analyze software test results and defect records, producing explainable GO, CONDITIONAL_GO, or NO_GO release-readiness recommendations with deterministic risk scoring, failed-test retrieval, defect hotspot ranking, and regression test planning.

Provides full control over GitLab epics, issues, merge requests, pipelines, and more via a conversational interface, with dry-run safety.

MCP-native release confidence control plane that turns browser execution into auditable go/no-go decisions by combining business-critical journey context, evidence-heavy QA runs, and risk governance.

A comprehensive MCP server with 53 tools for managing Jenkins CI/CD operations, including job, build, pipeline, node, credential, and plugin management, enabling AI assistants to control Jenkins servers through natural language.

AI-native control plane for Kubernetes and GitOps. Provides 30+ tools for service deployment, database provisioning, and log management via natural language.