Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Descripción del creador (original en inglés)
Self-hosted AI agent for office work: run agents, office tools and documents from any MCP client.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Descargar el archivo .mcpb del creador
El enlace lleva al archivo del propio creador; no lo alojamos ni lo reempaquetamos. Abre el archivo y Claude Desktop lo instalará.
Ejecuta esto en tu terminal
Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub Graphene-Lab, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (26.11.3) llegó al registro hace 3 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas MCPB, Docker en tu computadora.
En la misma categoría: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Agent-Native Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Add agentic power to your work! An AI personal assistant that automates tasks and your work without sacrificing privacy. We're happy to put this powerful tool in your hands to automate your business while reducing staff costs, providing you with the most advanced AI technology in the office automation industry.
AgentBridge is a self-hosted server that runs its own AI agents behind two primary interfaces in a single process: a full-screen chat terminal (TUI) and an HTTP API that speaks the standard OpenAI protocol, so any OpenAI-compatible client drives the same agents.
Chat in the terminal while scripts, bots, and apps use the same agents on the same port: same process, same conversations, no bridges, no synchronization.
To be explicit about what the compatibility is and is not: AgentBridge is OpenAI-standard on the outside, not on the inside. It *is* a standard OpenAI server to any OpenAI client — SDKs, bots and scripts talk plain POST /v1/chat/completions and reach the same agents. It does not run on a standard agent system: the agent core is our own engine (AIOrchestrator/AgentHarness), and its defining concept is that an agent's abilities are compiled .NET assemblies loaded as plugins from the Tools/ folder and driven in-process — no interpreters, no remote tool servers, no standard agent glue between the agent and its actions. That is the Universal Tool System described below, and it is the architectural difference that sets this product apart.
It is the first agentic harness system for next-generation artificial intelligence that introduces significant innovations, raising the bar for all competitors in the industry. The system encapsulates agentic functions in a well-designed sandbox that prevents companies from suffering damage from an AI that is not properly controlled, while at the same time allowing them to entrust real business tasks to the AI, with a very high level of privacy and confidentiality.
AgentBridge stands apart from the harnesses you are familiar with because it is designed to let even people with no technical skills — your grandma, for example — use it without risking damage: file actions are reversible thanks to versioning, the agent is confined to a space bounded by guardrails built in by design, and no code-agent features are provided, precisely to prevent code from being created or executed. It can also be supplied together with our cloud platform, which synchronizes the file area in real time with a private, encrypted cloud located within your own company. In short, it is a product any employer can make available to their employees to support office work and make business processes more efficient. With traditional harnesses, a badly worded prompt could destroy documents, wipe the work drive, or cause other kinds of damage; our focus, by contrast, has been on creating a safe tool for office use.
Why teams choose this architecture
AgentBridge is built on the AIOrchestrator library model: one runtime, one agent core, and one consistent operational flow across terminal and API. The result is faster execution, lower integration overhead, and stronger control than traditional multi-server MCP setups. Read the white paper: Why the AIOrchestrator Library Model Outperforms Traditional MCP Deployments.
AgentBridge is not a single project. It is a solution — a set of .NET projects that form one whole — and the repository you are reading is only the *host* that assembles it. The other pieces live in repositories of their own, and each one is a plugin: a library that gives the agent one family of abilities.
| Layer | What it does | Where it lives |
|---|---|---|
| AgentBridge — the host | Terminal UI, OpenAI-compatible API, sessions, voice, TTS, Telegram and SIP bridges, OfficeManager | this repository |
| AIOrchestrator / AgentHarness — the core | The agent loop, the deterministic memory, and the tool contract every plugin implements | Graphene-Lab/AIOffice |
| The plugins — the abilities | One compiled library per domain: Word, Excel, PowerPoint, PDF, podcasts, CAD, maps, ERP, Odoo, Power BI, Markdown | one repository each — list below |
| The support libraries | Deterministic code intelligence that reads a compiled assembly and derives its tool interface from it | UISupportGeneric · GiraffeAI |
flowchart TB
subgraph Host["AgentBridge — the host (this repository)"] TUI["Terminal UI · Web GUI · API"] LOOP["Agent loop (AgentHarness)"] end subgraph Plugins["Tools/ — the plugins folder"] DOC["OfficeTool → .docx .xlsx .pptx .pdf"] WORD["DocumentTool → Word"] SHEET["SpreadsheetTool → Excel"] DECK["PresentationTool → PowerPoint"] MORE["PodcastTool · MapTool · FreeCADTool ErpTool · OdooTool · PowerBITool …"] end TUI --> LOOP LOOP -- "direct method call in-process, no protocol" --> DOC LOOP --> WORD LOOP --> SHEET LOOP --> DECK LOOP --> MORE
No project references a plugin at compile time. The host hands the agent tool *names*; the plugin host scans the plugins folder (Tools/, next to the executable) at startup, loads the assemblies and resolves those names to real types at runtime — then hot-adds any plugin that appears later, 30 seconds after it lands. Adding an ability means dropping a folder in: no rebuild, no registration, no service to start, no schema to keep in sync.
The mainstream way to make an agent agentic is MCP: the model speaks JSON-RPC to a separate process, which does the work and answers. AgentBridge does the opposite, and that is why this product is a solution of libraries instead of a bundle of servers.
The agent uses the library directly. It has to create or modify a Word document? It calls the library that edits Word documents — exactly the way any application calls a low-level library — and gets the result back as a value, in the same process, as a native method call.
Concretely, what changes:
/tools, from tools.json, or from the tools field of an API request.MCP solved a real problem: reaching software you cannot link against, written by someone else, running somewhere else. As the *general* architecture of a system you build yourself, though, it puts a protocol where a function call belongs, and pays for that in latency, in configuration and in context window. Here the software is ours, it is compiled, and it sits on disk — so the agent gets the libraries themselves, and the architecture the agent follows is the one programmers already use.
MCP stays in the product as an interoperability channel, not as an internal one: outside clients can drive these agents over MCP (Use AgentBridge as an MCP server), and the agent can reach third-party MCP servers it is given. What it never does is speak MCP to its own abilities — those are assemblies, called directly.
The plugins — each a repository of its own, each a compiled library:
Writing one yourself is the whole integration: derive from BaseAgentTool, build, drop the folder into Tools/, and the agent can use it. How the pieces fit together — the system tools inside the engine, the plugins loaded from Tools/, and how a name becomes a type — is described in AgentBridge → AIOrchestrator → tools.
The Download for your OS button detects your platform and starts the right archive (~460 MB, self-contained — no .NET installation needed, Kokoro TTS voices included). Prefer the terminal? One line is enough:
| Platform | One-line install | |
|---|---|---|
| Windows (PowerShell) | `irm https://graphenelab.it/AgentBridge/install.ps1 \ | iex` |
| Linux / macOS | `curl -fsSL https://graphenelab.it/AgentBridge/install.sh \ | bash` |
The one-liners download the latest release for your platform into
Solo se muestra el principio; lee el resto en el repo