"Exposing a markdown folder as an MCP server for Claude" matching MCP servers:

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables LLMs to inspect and test other MCP servers by listing and calling their tools, reading resources, and getting prompts. Supports stdio, SSE, and HTTP transports for both local and remote MCP server inspection.

MCP server that enables Claude Code to send code and plans for review by OpenAI Codex, returning structured feedback inline.

MCP server providing code review, auto-fix, test running, linting, formatting, and refactor suggestions for Claude Code.

Enables Claude to capture screenshots of the screen, windows, regions, and web pages, and compare screenshots for visual regression testing.

.FAF (Foundational AI-context Format) with 50+ tools - Only Persistent project context that integrates seamlessly with Claude Desktop workflows. Officially merged (#2759) Anthropic MCP server.

Enables AI-powered automated testing, security scanning, code review, and maintenance tasks directly within Claude Code or desktop.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

Enables Claude Code to score its tool-calling transcripts for hallucinated action claims, unsafe edit ordering, redundant tool-call loops, and pass@k across repeated attempts at a task.

Connects Claude to AI/ML evaluation harnesses, token latency profilers, and prompt security red-teaming tools, enabling model benchmarking, latency profiling, and security assessment through MCP tools.

MCP server for Claude Text Lab, enabling fact-preserving regeneration of Claude-generated text through inspect, sanitize, audit, rewrite, and benchmark operations, with auditable local quality gates and an unverified provenance verdict.

Zero-sidecar MCP server embedded directly in the Godot 4 editor as a GDScript EditorPlugin — no Node or Python sidecar. Reflection-driven tools over any engine class, validate-before-write GDScript, scene/script/resource authoring, and a runtime play-test loop (play, screenshot, input, assert).

Enforces 21 critical rules derived from 96+ documented failure patterns to prevent common AI assistant mistakes. Provides automatic compliance checklists, rule summaries, and auto-updates.

Enables users to query, create, update, and manage Digital.ai Agility assets through MCP tools, with secure Windows Credential Manager authentication and configurable write operations.

Enables agents and tools to access Markdown linting through the Model Context Protocol, providing structured lint results and workspace-aware checks.

Provides a read-only MCP bridge that lets Claude Web inspect workspace files, git state, and recorded test results while Codex remains the sole executor of changes.

Enables AI assistants to operate directly inside a running Unity Editor project, creating scenes, generating scripts, simulating input, capturing screenshots, inspecting performance, and automating editor tasks through its built-in tools and resources.

Generates a pytest suite from acceptance criteria withheld from the coding agent, so the tests can disagree with the code; qikly_run never returns the criteria. The CLI also scores an existing suite by planting faults, and ships as an agent Skill (qikly --install-skill). Runs locally (uvx --from "qikly[mcp]" qikly-mcp): your code and API key stay on your machine.

Enables Claude to build and preview mobile apps on multiple iOS and Android devices simultaneously, with live streaming and touch control, all via MCP.

MCP server that brings Trustabl static reliability scanning into Cursor, letting agents inventory agents/tools, flag risky patterns, score production readiness, and write SARIF reports.

A reference MCP server that enforces identity-aware tool access using role-based permissions (Reader, Analyst, Auditor) and supports multiple identity routes like Entra RBAC, Copilot Studio, and Okta XAA. It provides read-only access to test evidence with explicit denial paths for unauthorized tools.

Enables Claude to independently check an AI agent's work in a local git repository by recording a baseline, running only the checks relevant to the changed files, and cross-checking what the agent claimed. Returns a compact, evidence-labelled report with a verdict and a ready-to-paste next prompt, so unverified success claims can't slip through.

Zero-dependency MCP server and CLI that proxies, inspects, and analyzes JSON-RPC message streams between MCP clients and servers.

Lets Claude design, run and compare local robotics experiments — swarm behaviours, formations, coverage, cooperative localisation and synthetic visual odometry — through tools for cataloguing worlds, launching runs and campaigns, tuning parameters, saving floor plans and diffing metrics. Everything executes on the user's machine via a stdio JSON-RPC process, so runs are reproducible and no data leaves the host.

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 checking npm packages for known security vulnerabilities using the OSV API before installation. Supports both single package checks and bulk vulnerability scanning for multiple packages at once.

A simple server implementing the Model Context Protocol (MCP) that echoes messages back, designed for testing MCP clients.

Single MCP server providing over 500 developer tools for Claude Code, covering security, testing, documentation, and more.

Bridges AI models with WinDbg to analyze Windows crash dumps and perform remote debugging through natural language queries, enabling execution of debugger commands and automated crash analysis.