A local, stdio-based MCP server that lets AI agents create and maintain a brand project through typed tools covering identity, palette, typography, voice, assets and guide chapters, then validate it and export a self-contained, client-facing static guidelines site that can be hosted anywhere.

Enables coding agents to propose, review, promote, and verify architecture changes as recorded C4 model updates, with hypothetical diffs, evidence-based qualification, and component histories.

Lets AI coding agents build, test, and lint Android projects with Gradle, control devices and emulators via adb, automate UI through screenshots and input injection, and use a live IDE bridge for refactoring, code inspection, and run configurations. Works with any MCP client over stdio or authenticated HTTP.

Equips AI coding agents with searchable production incident scenarios, outside-in diagnostic runbooks, interview elevator pitches, hardened Kubernetes manifest generation, CLI cheat sheets, and cloud architecture blueprints.

Provides a shared, repo-local memory that lets coding agents recall relevant decisions, conventions, gotchas, and open threads, save new entries, coordinate file claims, and cache file summaries across tools and sessions.

Enables AI assistants to scan-code log into Yuketang and read-only browse courses, slides, classroom replays with page-flip timelines, AI mind maps, notes, and assignment progress. Sessions can be supplied via QR login or environment variables, with separate handling for the four Yuketang regional deployments.

Enables AI IDEs and assistants to perform AST analysis, map dependency graphs and call chains, run semantic code search, and optionally sync cloud-backed memory — all locally so source code never leaves the machine.

Exposes 16 local stdio MCP tools that give Codex-style clients project-isolated persistent memory, local ONNX-based semantic search, and durable task tracking that survives across sessions and concurrent clients, without executing agents, hosting a model, or contacting model providers.

Enables running NXOpen journals and Python scripts inside an already-open Siemens NX 2512 session from chat, with tools for pinging/checking the live bridge, creating and opening parts, and listing modules. It also adds a left-sidebar NX panel showing the bridge endpoint, available tools, and copy-ready commands.

Enables keyword search across source-traceable evidence chunks, listing opportunities linked to supporting evidence, and deterministic ROI calculations with model-proposed inputs and TypeScript-computed dollar figures.

Checks a site for AI crawlers: which of 11 AI crawlers its robots.txt lets in, whether its llms.txt follows llmstxt.org, and what its home page says without scripts. Findings with evidence; no scores, no model calls, no telemetry.

This MCP server enables agents to administer a self-hosted AI control plane for users, organizations, subscriptions, API keys, model providers, and service health, with local-first model routing and cloud failover.

Enables AI hosts to retain evidence, check explicit constraints, plan bounded work, and record outcomes through local-first MCP operations. Optional reconstruction tools also support experimental image-to-3D workflows with local model providers and Blender.

Enables coding agents to record product demos, changelog GIFs, help-center guides, and bug repros by driving a signed-in browser or Mac window, then rendering branded MP4 and GIF outputs with delivery checks.

Embeds a runtime MCP inspector in a NestJS app so coding agents can inspect the module and provider graph, routes and their guards/interceptors/pipes/filters, logs, request traces, event listeners, and scheduled jobs through an HTTP endpoint.

Enables evidence-first AWS architecture work through deterministic design calculations, live official AWS knowledge, integration catalog/configuration, and optional authenticated local read-only AWS tooling for requirements, comparisons, diagrams, ADRs, and operational planning.

Enables users to search and read recruiter Gmail, classify and label threads into categories, archive confidently categorized mail, and create reply drafts for manual sending, while never sending mail or auto-archiving uncertain messages.

Turns any OpenAPI spec into a single-tool MCP server where the model writes JavaScript against a typed api object in a QuickJS sandbox, so multi-step tasks run in one round trip and only the final result reaches context. Credentials, rate limiting, retries, write gating and audit logging stay on the host, outside the sandbox.

Enables MCP clients to create and control persistent, PTY-backed terminal sessions on macOS: launch commands and interactive programs, read output incrementally via byte cursors, send keystrokes, wait on conditions, and detect running/awaiting-input/exited states. Sessions run inside a Seatbelt sandbox with command policies, human approvals, secret redaction, and hash-chained audit logging.

Enables agents to probe URLs and classify bot-wall responses with vendor and signal evidence, perform offline classification, scan for exposed key-like material, and run owner-side access audits through stdio tools.

Enables an LLM to orchestrate multiple downstream MCP tools inside one isolated sandbox in a single turn, filtering intermediate results in memory and returning only the final output to cut context tokens.

Enables AI agents to query Korean public data from OpenDART, data.go.kr and law.go.kr — corporate filings and financials, stock prices, apartment trades, business registration status, holidays, statutes in force on a given date, and court rulings. It corrects the live APIs' known traps (mislabeled periods, not-yet-in-force laws, cancelled trades, changed district codes) so answers come back right, with evidence.

Lets any MCP-capable AI agent call a hosted EdgePress site's REST API to browse and manage CMS content or store data, using a personal access token whose role and read-only flag decide what the agent can do. Supports Streamable HTTP at /api/mcp or local stdio via npx, with an OpenAPI spec lookup tool for discovering routes and request bodies.

Enables MCP clients to run provider-backed reverse-engineering and software-analysis workflows for source code, binaries, and architecture, with evidence, limits, and optional external tool integrations.