"A command-line fuzzy finder" matching MCP servers:

Enables AI coding tools to scaffold, build, and deploy Node.js or Python apps to Varity with a single command, automatically provisioning databases and backend services.

tailtest-cline is a Cline plugin that automatically generates and runs tests every time the agent edits a source file. https://github.com/avansaber/tailtest-cline

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.

Enables AI agents to retrieve the latest semantic version tags for container images from Docker Hub, GHCR, Quay, and other OCI registries, allowing them to pin specific versions for reproducible deployments.

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

MCP security trust layer. Continuously monitors 800+ MCP packages on npm for install scripts, command injection, hardcoded secrets, capability drift, and publisher posture. Ships a GitHub Action policy gate for PR-level allow/warn/block decisions. 5 MCP tools, no API key required.

Enables agents and CI pipelines to audit MCP servers and agent tool-chains by statically scanning repositories, local checkouts, tools/list exports, or live endpoints for risks such as destructive actions without confirmation, mismatched safety annotations, injection surfaces, credential or PII exposure, and unguarded command, path, or URL sinks. All checks are read-only and never execute the scanned code or call tools/call.

AI Gateway - MCP server providing AI-powered tools and automation by MEOK AI Labs

A GitHub-native secrets manager that allows AI assistants to securely manage, generate, and validate credentials without exposing sensitive values in conversation history. It supports secret scanning, environment diffing, and secure command execution by injecting masked variables directly into the runtime environment.

Generates comprehensive API test plans (positive, negative, and boundary cases) from endpoint metadata and exports them as Excel files.

A specialized MCP server for QA engineering. It provides tools for user story analysis, test strategy, BDD/Gherkin scenarios, contract testing, integration tests, performance plans, security checklists, and CI/CD pipeline generation, accessible from any MCP-compatible IDE or client.

A demonstration MCP server built with FastMCP v2.0 that provides basic mathematical calculations and greeting functionality. Features Docker containerization, comprehensive testing, and CI/CD automation for learning MCP development patterns.

Forces every AI Agent code change (Claude Code, Cursor, Trae) to leave a structured problem/reason/approach audit record before commit. 11 MCP tools with full annotations, pre-commit hook blocks unaudited changes. Local stdio, no API key, MIT. M8ven Trust 100/A.

Self-hosted coding agent that runs Claude Code or Codex in your own infrastructure and works from Slack. Exposes codebase investigation, file edits, branch and PR creation, allowlisted command execution, CI status and an audit log as MCP tools, keeping every credential behind the tool layer instead of handing it to the model.

Integrates Ploi.io API functionality into AI assistants for managing servers, sites, and databases through natural language. It enables features like one-command deployments, project linking, server log retrieval, and database backup management.

Enables LLM clients to access DevSecOps tooling such as CI/CD pipeline status, vulnerability triage, log search, and dependency scanning through MCP, turning AI copilots into security-aware engineering partners.

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.

Enables SSH-based deployment operations such as git pull, command execution, script upload/run, and SSH config management.

Enables intelligent access to AL-Go documentation, workflows, and domain expertise for Business Central development automation through specialized personas and cross-source semantic search.