"A server for orchestrating intelligent agents to solve spatial reasoning tasks in 3D environments" matching MCP servers:

An MCP server that gives AI agents geometric spatial awareness of web page layouts using Playwright, enabling detection of visual occlusion, layout shifts, and spatial relationships.

Gives headless CAD agents a deterministic, dependency-free STL audit that checks manifoldness, plate grounding, single-shell structure, wall thickness, and normal orientation, returning a printable verdict with a critic score. Enables agents to gate and iteratively repair generated meshes before slicing or printing.

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

Enables AI agents and MCP clients to drive real Chrome, Edge, Brave, and Firefox browsers through native automation protocols. It exposes tools for navigation, page snapshots, form filling, clicks, screenshots, console/network inspection, and tab management.

Enables MCP clients to open websites, capture screenshots at multiple breakpoints, and run automated design audits for issues like overflow, small tap targets, low contrast, missing alt text, tiny text, and clipped content.

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.

Enables AI agents to inspect UI screen recordings as token-efficient image sheets with changed regions boxed, single-frame flicker flagged, and speech aligned to frames. Exposes watch_video and zoom_video tools so agents can pull dense keyframes across any time range or one sharp full-resolution frame, all processed locally.

Enables MCP clients to run and track scans, inspect quota usage, redeem existing studio report rights, and list or download generated reports through the associated REST API. It operates locally over stdio with API-key authentication and bounded retry/polling behavior.

Enables automated QA testing by running a pipeline of AI agents that generate test scenarios, architect test layers, write Playwright tests, and review code, all grounded in feature requirements and API contracts.

Enables agents to turn a plain-language description of a device into a complete, validated build package — parts list, 3D-printable parts, wiring, firmware code, picture assembly guide, and tests — that anyone can assemble without electronics experience.

Enables turning requirements documents into RFCs, functional test scenarios, and a traceability matrix, with tools to parse, diff, and verify coverage.

Automates the conversion of Figma designs into TypeScript React components and integrates with GitHub to create pull requests for the generated code. It includes visual regression testing with Playwright and accessibility validation to ensure implementations match the original designs.

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 AI assistants to read, query, compare, edit, QA/QC, and export RISA-3D .r3d structural models through natural language, with a standalone CLI for local diagnostics and reporting.

A deterministic verification gate for MCP clients that independently checks model outputs against evidence, contradictions, calibration, and provenance without relying on LLM self-assessment.

Provides a testable gateway path for running a local MCP-style server in hosted-like conditions, with tenant-isolated reads, approval-denied writes, deterministic failures, and smoke-test verification.

Enables AI agents in Copilot Chat to autonomously plan, generate, and self-heal Playwright UI and API tests by connecting to a local browser runtime.

Free JSON Schema validation, JSON to TypeScript, CSV to JSON, JSON repair and JSON to CSV for AI agents. Hosted MCP plus local STDIO. Connect once with a scoped key; enforce tool allowlists and quotas, inspect request IDs. Runnable repair → validate → CSV workflow. Bounded OpenAPI and webhook checks. No LLM calls or payments. Setup: invokeport.com/agents.

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).

Integrates ProjectDiscovery security tools to perform automated reconnaissance, subdomain discovery, and vulnerability scanning. It enables comprehensive bug hunting workflows by chaining tools like subfinder, naabu, and nuclei into a unified pipeline.

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

Enables AI assistants to surgically extract and analyze code, reducing token usage and costs by up to 200x compared to reading entire files.

Enables AI agents to submit code files for analysis and receive rule-based findings with severities, line numbers, and SARIF fingerprints, covering security, complexity, and dependency/configuration drift.

Enables free, read-only checks of AI agents and MCP servers for conformance, published changes, delivery evidence, and verifiable receipts without requiring an account or API key, using public or non-personal data only.

MCP server for remote debugging of Apps in Toss mini-apps, providing CDP relay and test runner capabilities.

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 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.

Enables LLMs to perform browser automation tasks including web scraping, taking screenshots, and executing JavaScript using Playwright. It facilitates real-time interaction with web pages and the generation of automated test code.

Enables AI agents to perform end-to-end web testing by controlling a real browser through tools for navigation, interaction, state inspection, screenshots, and script evaluation.

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.