Enables Claude Code users to inventory the MCP servers, skills, commands, agents and plugins installed on their machine, estimate how many tokens each one adds to every request, and switch them off per project or globally, including across other AI coding tools. It also monitors live sessions to report real token usage and the savings achieved from disabled items.

Lets Claude and other MCP clients hand coding tasks to the Codex CLI as a sub-agent, running under the user's own Codex configuration so any configured model provider (OpenAI, DeepSeek, local models) does the work. Provides tools to start, poll, cancel and inspect jobs with compact change summaries, long-task handling, token-saving lean mode and clean process teardown.

Enables AI agents to log into the SIGAA academic system through its web interface and read a student's data: portal info, enrolled and past classes, course topics, participants, grades, attendance, assignments, exams, news, forums, and course plans. It also lets agents download course files and participant photos on demand.

Enables AI agents to manage to-dos, lists, schedules, recurring tasks, and notes through standard stdio MCP tools, sharing authentication with the companion CLI and discovering business tools after login.

A stdio MCP server that lets AI coding tools on a Mac speak text aloud through the local Speaklna text-to-speech app. It exposes four tools (speak, stop, status, voices) so agents can voice replies, halt playback, check state, and list available voices, but cannot import voices or change settings.

Enables coding agents to explore a database through the project's Drizzle schema, with tools for schema inspection, row browsing, counting, read-only SQL, query plans, drift and migration checks.

Drives the local Doubao desktop client through its DevTools interface, letting an agent read and send chats, run task-mode work, hand off a project directory and take it back, and call Doubao-only capabilities like image generation and step traces. Also borrows Doubao's built-in skill set for cross-checking and project handoff, with a UI badge showing which side currently owns the work.

Enables AI agents to queue, commit, push, and track durable Git transactions through a shared daemon, preserving other agents' unstaged work and allowing recovery by request ID.

Virtual keyboard and gamepad for AI agents on Linux / Steam Deck — zero-dependency uinput daemons with an MCP server interface.

SceneScout — exploratory UI testing for AI coding agents. An MCP server that gives any agent (Claude Code, Cursor, VS Code Copilot, Codex, Gemini CLI and others) a structured view of a running web app, always-on oracles, a network-level write policy, memo

Enables Claude Code to delegate tasks to persistent GitHub Copilot CLI sessions via MCP, inspect pending tool requests, and approve each operation once or deny it while continuing multi-turn context. It bridges ACP runtime sessions locally over stdio without a public service or background daemon.

Enables agents to scan course structures, play videos at real 1x speed, track document task completion, capture quiz screenshots for vision-model reading, select and submit answers, and verify scores through MCP tools.

Enables listing models and running non-streaming chat completions against RelayRouter's OpenAI-compatible API, so agents can discover available models and send chat requests through a key-configured MCP endpoint.

Enables an external AI client to discover tender portal APIs, collect and verify tender listings, combine sections, and select relevant lots from a user request through local MCP tools.

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.

A local stdio MCP server that enables coding agents to find licensed photos and icons, generate color palettes and simple SVG assets, and preview static web prototypes. It also supports editable agent skills for design and prototype review workflows.

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.

This MCP server lets an agent run local binary inspection on ELF, Mach-O, PE, APK, IPA, ASAR, WebAssembly, and firmware targets — pulling symbols, sections, classified strings, disassembly, and mitigation posture, and flagging dangerous imports and CWE patterns. It exposes eight stdio JSON-RPC tools (with no external API keys) that feed a multi-agent swarm for attack-surface mapping and exploit-chain synthesis.

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 agents to discover, search, compare, and inspect tested MCP tools by problem or keyword, with certification verdicts, scorecard summaries, certified scope, and explicit not-tested details.

Enables AI agents to make policy-scoped payments with spending caps, recipient allowlists, approval thresholds, instant revocation, and an append-only audit trail in a sandbox wallet.

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.