Prototype · Preview: every server in the official registry, synced every 30 minutes. Reviews and accounts come in a later step.
PopNx MCPMCP servers for people who use AI · explained in plain words

~alter mcp-ollama

by true-alterversion 0.2.1i★ –iRuns on your computer
Registry nameio.github.true-alter/mcp-ollama

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

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

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account true-alter, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 18685 servers in this category
  • Published to the registry more recently than 31% of the other 18685 servers in this category
  • Basic checks equal to or better than 100% of the other 18685 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is ~alter mcp-ollama safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.1) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Bestax

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

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

by formulahendryEarly↓ 66/wk★ 440Updated 14 months ago

Runs on your computer

Remote Desktop Commander

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

by desktop-commanderGrowing★ 211Updated 4 days ago

Runs in the cloud✓ desktopcommander.app

Bestax

Props, examples, CSS variables and Agent Skills for bestax-bulma React components (Bulma v1)

by allxsmithGrowing↓ 2.9K/wkUpdated today

Runs on your computer

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

~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

Only the beginning is shown; read the rest in the repo

Ask PopNx