프로토타입 · 미리 보기: 공식 레지스트리의 모든 서버를 담고 있으며 30분마다 동기화해요. 리뷰와 계정 기능은 다음 단계에서 열려요.
PopNx MCPAI를 쓰는 사람을 위한 MCP 서버 · 쉬운 말로 설명해요

~alter mcp-ollama

제작자: true-alter버전 0.2.1i★ –i내 컴퓨터에서 실행
레지스트리 이름io.github.true-alter/mcp-ollama

설치

개요

제작자가 쓴 설명(영어 원문)

Wraps local Ollama models so bulk generation runs on your own hardware, not a paid API.

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
  • 카테고리: 기타

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.

필요한 것

  • npmNode.js 설치(npx 명령어용)

어떤 앱을 쓰세요?

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

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

{
  "mcpServers": {
    "ollama": {
      "command": "npx",
      "args": [
        "-y",
        "@truealter/mcp-ollama"
      ]
    }
  }
}

터미널에서 이 명령어를 실행하세요

claude mcp add ollama -- npx -y @truealter/mcp-ollama

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "ollama": {
      "command": "npx",
      "args": [
        "-y",
        "@truealter/mcp-ollama"
      ]
    }
  }
}

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

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "ollama": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@truealter/mcp-ollama"
      ]
    }
  }
}

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 8일 점검

  • ✓ 통과

    제작자와 저장소 일치

    레지스트리 이름이 GitHub 계정 true-alter 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

기타 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 18398개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 18398개 중 31%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 18398개 중 100%와 같거나 더 좋아요

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

자주 묻는 질문

~alter mcp-ollama, 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(0.2.1)은 2개월 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

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

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Tethered Trust

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

Spec Driven Development

제작자: formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

내 컴퓨터에서 실행★ 440MIT14개월 전 업데이트
설치

Remote Desktop Commander

제작자: desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

클라우드에서 실행★ 2113일 전 업데이트
설치

Tethered Trust

제작자: tetheredtrust.com

Fit, compatibility and recall checks for AI agents before they buy: verdicts, evidence, receipts.

클라우드에서 실행오늘 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.

~alter mcp-ollama

Hands the work that shouldn't leave your machine to the model already sitting on it

What it does · Install · The tools · Why this sits under ~alter

What is mcp-ollama?

An MCP server that hands work to Ollama on the same machine and passes the answer back. Ten tools over stdio. Your client calls one of them, Ollama does the generating on your own GPU, and nothing is charged to an API account.

Most of a working session is mechanical. Docstrings, commit messages, PR descriptions, changelog entries, classification and tagging, summarising a long file, converting one format into another, and having a small vision model look at a screenshot and report what's on screen. None of that needs a frontier model, and most of it gets one anyway, because that's what your client already has an API key for.

Hand it a staged diff and a commit message comes back. Hand it a chunk of source and you get a docstring, a test stub or a set of type annotations. All ten tools, and what each one takes, are in the tools.

The orchestrator decides what gets routed here. This server makes no judgement about what belongs local, and it doesn't stream, queue or cache. It keeps nothing between calls beyond a random identifier for the process it's running in.

It depends on two things and ships neither. Node 18 or newer runs it, and a running Ollama with at least one model pulled does the actual generating. There are no weights in this repository and no download of weights at install time. The default model is hermes3:8b, which you can override per call or per environment.

Why this sits under ~alter

You already decided that some work stays here. That's why there's a model on this disk, pulled once and left there, instead of an API key doing the same job from a datacentre you'll never see. ~alter starts from the same decision and points it at the other thing that leaves your machine constantly, which is the record of who you are.

Nothing on this machine answers that well today. Your account is a password at a login screen and a token in a config file, and each of those checks one moment and then stops looking. The years of work that actually say who you are sit outside anything either of them can see. An agent commits under your name now, in your editor, and when somebody asks later who allowed that, there's no answer written down anywhere.

~alter answers that with a handle. ~yourname, one of them, carrying a record built out of work you actually did. A client speaking the protocol picks it up without being configured again, much the way this server picks up a model you pulled once and left on the disk.

You bought hardware to stop paying per call. On that record the per-call money runs the other way. The bare fact that you exist is free for anyone to check, depth past that is charged to whoever wants it, and you're the one who decides which readers reach which depth.

None of it is needed here. mcp-ollama has no login and asks for no handle, and it behaves the same whether you hold one or not. There's one small wire between them and it's worth naming plainly. If the ~alter runtime happens to be installed on this machine, every local generation appends a single line to a file in your own home directory, recording that the work ran here at no API cost. That line never goes anywhere, and if the runtime isn't installed no line gets written at all.

I want to know more Your friends do not know you from a login. Neither does your family, or the people you work with, or your sports team. They know who you are from how you have shown up, over years. You may look and sound nothing like you did ten years ago and it is still you. Software still asks the narrow question. A password at the login screen. A token in the app. Each one checks whether this is the right person, right now, at this exact spot, and then looks away. Everything in between is invisible to it, and that is almost all of your life. The AI tools made it worse, because one of them writes in your name now, and when somebody asks who allowed it, there is no answer anywhere on this machine. One name, and the record under it is yours. ~yourname works at every tool that speaks the protocol, so nothing is set up twice and there is no key to paste, at any point. What is in the record was read from what you did, not typed into a box by you or guessed at by a model. You can cut off access to any of it with one command. No form, no review. Being read pays you. Anyone can check for free that your handle exists. Reading further, past the fact of you, costs the reader money, that money goes to you, and you decide who gets to read what. Collectives hold a record on the same terms, because it is one record at every scale and the same form holds you, your team, and your country. A union, a club, a trade body, or a group of people who have never met can vouch for their own members and be read the same way you are. Threads are how you get somewhere. A thread is something you are working towards. You take one on yourself, or ~Alter plants one from what it can already see, or a collective confers one on you. What gets read is the trail you leave while you are doing it, never a certificate at the end. All of that is the short version of an argument set out properly, in eight chapters at truealter.com/origin . Its seventy-six predictions were each written so the data could come back and say no. Five of them did, and those five are still published alongside the rest.

I want to check it myself

None of it needs taking on trust. Hand this to the AI you already use and let it take you through in your own words.

Go to truealter.com, find the genesis and the origin papers, and read all of

them. Then start a discussion with me in my own language, no jargon.

Ask me one question at a time and wait for my answer. Follow what I am curious about, not the order the site is written in.

Do not only read the pages. Connect to their interface directly and call get_started. That tells you where I am and what comes next, and we work the rest of this from there.

If I have a ~handle I will give it to you. If I do not and I decide I want one, set it up with me here.

What I want to understand is what ~Alter is, how it applies to me, and what it means for everyone else. Find me somewhere in it, and not the version written for people who work in technology. Find the life nearest mine and walk me through it, including what it would cost me.

Try to prove them wrong. Go and find where they show their working, and if something is unclear or does not hold up, say so.

The ~alter command line is where a person meets ~alter, and this isn't that. mcp-ollama has no command of its own worth typing and never asks you to log in to anything. It's a process your MCP client starts and stops, and it happens to be maintained by the same people.

Install

npm install -g @truealter/mcp-ollama

That puts one command on your PATH, mcp-ollama, which is the process your client launches. The package ships the build already done, so there is no compile step and no toolchain to have installed first. CI builds it against Node 18, 20 and 22 before publish, so anything in that range is known to work at runtime.

If you would rather install nothing at all, npx -y @truealter/mcp-ollama fetches it on first use and runs the same process. That is the form used in the client configuration below.

The scoped name is the one to type. The unscoped mcp-ollama on the public registry belongs to an unrelated publisher and is not this package.

Nothing is installed as a service and nothing runs in the background. Your client starts the process when it needs it and stops it when it is done.

Routing your first job

1. Pull the model it reaches for by default
ollama pull hermes3:8b

That's the default this server reaches for when a tool call doesn't name a model. It's quick and it's honest at classification, tagging and short generations. Heavier models are worth having for code work, and choosing a model covers when to bother.

2. Register the server with your client
claude mcp add --transport stdio ollama -- npx -y @truealter/mcp-ollama

If you installed globally, -- mcp-ollama works just as well and skips the fetch. Cursor, Cline and anything else MCP-aware take the same shape in their own config. The client launches the process; you never run it by hand except to debug, and if you do, it sits there waiting on stdin, which is correct rather than broken.

3. Ask your client what is on the host
List the models on the local Ollama host.

Say that to your client in whatever words you like. It resolves to local_models, which reads Ollama's tag list and reports each model's size, parameter count, quantisation and family. If what you just pulled comes back, the wire is good end to end.

4. Hand it a diff and ask for a commit message
git diff --staged

Hand that output to your client and ask for a commit message. It routes to local_diff with commit-message, which prompts for imperative mood, a subject under 72 characters and a body explaining why rather than what. Nothing about that needed a frontier model, and now it doesn't use one.

The tools

ToolWhat it does
local_generateFree-form generation with your own system prompt, temperature and token ceiling
local_summarizeSummarise bulk text as bullets, a paragraph or one line, optionally focused on a theme
local_analyzeStructure pulled out of text, classification, entities or tags, in an output shape you name
local_draftFormulaic prose against a convention you supply
local_codedocstring, test, explain, review, types, comments or refactor-suggest over a chunk of source
local_diffcommit-message, pr-description, changelog, summary or impact from a diff
local_transformMechanical pattern transforms, format conversions, renames and syntax migrations
local_modelsWhat's on this Ollama host, with sizes and quantisation
local_pullPull a model onto this host by name, untagged names only
local_visionHave a vision model look at screenshots and report see, emptystate or legibility

Ten of them, and the full schemas come over MCP introspection, so any MCP-aware client enumerates them without being told.

Two take a max_tokens argument. local_generate defaults to 2048 and local_summarize to 1024. The rest set their own ceiling in code, 4096 for local_code and local_transform, 2048 for local_analyze and most of local_diff, 512 for a commit message, 1024 for local_draft. If output comes back cut short on one of those, split the input rather than hunting for a parameter that isn't there. Temperature is exposed on local_generate only.

local_vision is the odd one and worth a note. It reads pixels and reports what is on screen, whether the main content area holds real data or an error, which regions exist, what text

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