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AgentBridge

제작자: Graphene-Lab버전 26.11.3i★ –i내 컴퓨터에서 실행
레지스트리 이름io.github.Graphene-Lab/agentbridge

설치

개요

제작자가 쓴 설명(영어 원문)

Self-hosted AI agent for office work: run agents, office tools and documents from any MCP client.

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 내 컴퓨터에서 실행
  • 전송 방식: stdio, Streamable HTTP
  • 카테고리: 문서, 시트 및 사무 업무

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 1개 중 1개 통과
  • 내 컴퓨터에서 내 사용자 계정의 권한(파일, 네트워크, 앱)으로 실행돼요.
  • 레지스트리에 입력해야 할 키가 나와 있지 않아요.

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

제작자의 .mcpb 파일 다운로드

링크는 제작자의 파일로 바로 연결돼요. 우리가 보관하거나 다시 패키징하지 않아요. 파일을 열면 Claude Desktop이 설치해요.

터미널에서 이 명령어를 실행하세요

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 GitHub 계정 Graphene-Lab 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • – 해당 없음

    엔드포인트 응답

    내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요

  • – 해당 없음

    OAuth로 로그인

    내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요

문서, 시트 및 사무 업무 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 2174개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 2174개 중 88%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 2174개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

AgentBridge, 안전한가요?

해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(26.11.3)은 3일 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 MCPB, Docker도 있어야 해요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Agent-Native Calendar

제작자: BuilderIO

Agent-Native Google Calendar - manage events, sync, and public booking

클라우드에서 실행★ 7,620MIT2개월 전 업데이트
설치

Excel MCP Server

제작자: haris-musa

Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.

내 컴퓨터에서 실행★ 4,276MIT6일 전 업데이트
설치

MCP Server for Excel

제작자: sbroenne

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

내 컴퓨터에서 실행★ 847MIT3일 전 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

AgentBridge (codename "AGENT") — AI personal assistant that promises to replace humans in office work

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.

The architecture: one solution, and everything in it is a plugin

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.

LayerWhat it doesWhere it lives
AgentBridge — the hostTerminal UI, OpenAI-compatible API, sessions, voice, TTS, Telegram and SIP bridges, OfficeManagerthis repository
AIOrchestrator / AgentHarness — the coreThe agent loop, the deterministic memory, and the tool contract every plugin implementsGraphene-Lab/AIOffice
The plugins — the abilitiesOne compiled library per domain: Word, Excel, PowerPoint, PDF, podcasts, CAD, maps, ERP, Odoo, Power BI, Markdownone repository each — list below
The support librariesDeterministic code intelligence that reads a compiled assembly and derives its tool interface from itUISupportGeneric · 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 idea: the agent calls software, not a protocol

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:

  • No protocol hop. No second process, no HTTP round-trip, no serialization between the agent and its action: a tool call *is* a method call. The failure modes of a protocol — timeouts, transport errors, version skew between client and server — simply do not exist.
  • Granular control, not a reduced surface. The agent drives the real API of the library, not the handful of endpoints someone decided to expose: it can style a run of text, set a page break, keep a template's numbering — every parameter the library accepts.
  • Deterministic interfaces. The tool interface is derived from the compiled code, so the model is offered the methods that exist and only those: no invented endpoints, no drifting schema.
  • Type-safe errors. A failure arrives as a .NET exception that the harness catches and reports back in words the model can act on — not as an opaque protocol error.
  • Context economy. Only the plugins that are enabled exist for the agent. A disabled plugin is absent from the catalog entirely: it costs zero context tokens and cannot be hallucinated, because for the agent it does not exist. Abilities are not paid for twice — once in the prompt prefix on every turn, and again when they are unused. The agent cannot switch one on either: nothing in the tool set writes the tool policy, so what an agent is allowed to do stays your decision — taken from /tools, from tools.json, or from the tools field of an API request.
  • One artifact, no drift. The tool and the code it calls are the same assembly, built and shipped together.
  • A sandbox around every call. Every tool call passes through the harness, which enforces the action perimeter structurally — no plugin method can step outside it.

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.

Install & download

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:

PlatformOne-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

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