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~alter mcp-ollama

von true-alterVersion 0.2.1i★ –iLäuft auf deinem Computer
Name in der Registryio.github.true-alter/mcp-ollama

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

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

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: Läuft auf deinem Computer
  • Transport: stdio
  • Kategorie: Sonstiges

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

  • Basischecks: 1 von 1 bestanden
  • Läuft auf deinem Computer mit den Rechten deines Benutzerkontos (Dateien, Netzwerk, Apps).
  • Die Registry nennt keinen Schlüssel zum Eintragen.

Du brauchst

  • npmNode.js installiert (für den Befehl npx)

Welche App nutzt du?

Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.

Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein

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

Führe das in deinem Terminal aus

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

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

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

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

In VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

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

Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.

Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 8. Nov. 2026

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde mit dem GitHub-Konto true-alter bestätigt, dem das Repo gehört

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • – Nicht zutreffend

    Endpunkt antwortet

    Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen

  • … Noch nicht geprüft

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen

Im Vergleich mit anderen in Sonstigesi

  • Mehr Sterne als 0 % der anderen 18365 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 31 % der anderen 18365 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 18365 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist ~alter mcp-ollama sicher?

Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.

Welche Schlüssel oder Codes braucht er?

Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.

Läuft er auf meinem Computer oder in der Cloud?

Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.2.1) kam vor 2 Monaten in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Funooy Krillion Reference

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

Spec Driven Development

von formulahendry

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

Läuft auf deinem Computer★ 440MITAktualisiert vor 14 Monaten
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Remote Desktop Commander

von desktop-commander

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

Läuft in der Cloud★ 211Aktualisiert vorgestern
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Funooy trivia references in six languages, with rules and fixed scoring. No daily spoilers.

Läuft in der CloudAktualisiert heute
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README vom Entwickler

README öffnen

Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.

~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

Nur der Anfang wird gezeigt; den Rest findest du im Repo

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