~alter mcp-ollama MCP server

by true-alter·io.github.true-alter/mcp-ollama·v0.2.1

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

A91/100grade A

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A91/100

full report

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Growing

0 stars45 downloads/wk

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~alter mcp-ollama tools (10)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

local_analyze
Extract structured information from text locally. Use this for classification, entity extraction, tagging, pattern recognition, or any task that transforms unstructured text into structured output. Good for: categorising issues, extracting names/dates/amounts, tagging content, parsing semi-structured data, sentiment analysis.
local_code
Code-aware local generation. Claude reads source code with Read/Grep (free), then delegates the TEXT GENERATION to local - docstrings, test stubs, explanations, type annotations, inline comments, or review feedback. This is the primary tool for reducing API token usage on code tasks. Claude orchestrates (decides what code to read, what task to perform), but the actual generation happens locally at
local_diff
Analyse a git diff locally. Use this for generating commit messages, PR descriptions, changelog entries, or understanding what changed in a diff. Claude runs `git diff` (free), passes the output here for text generation. Particularly valuable for large diffs that would consume many API tokens if processed by Opus/Sonnet directly.
local_draft
Draft text locally - commit messages, PR descriptions, docstrings, changelog entries, documentation sections, or any formulaic text that follows a template or convention. Saves Opus tokens on boilerplate generation.
local_generate
General-purpose local LLM generation. Delegates work to a local Ollama model to save tokens. Use this when the task is bulk text processing that doesn't require Opus-level reasoning: summarising documents, explaining code for docs, generating boilerplate, reformatting content, translating, etc. The local model (default: hermes3:8b) runs on the user's hardware - zero API cost, ~40 tok/s on a decent
local_models
List all models available in the local Ollama instance. Use this to check what models are loaded and available for delegation.
local_pull
Pull/download a model into Ollama from the registry, or import a local GGUF file. Use this to make additional models available for delegation. For GGUF files, create an Ollama Modelfile first, then use 'ollama create'. This tool handles registry pulls (e.g., 'qwen2.5:14b', 'deepseek-r1:8b').
local_summarize
Summarise long text locally. Use this instead of having Opus process large blocks of text when you only need a summary. Feed in file contents, docs, logs, or any bulk text and get a concise summary back. Particularly valuable for: large file contents, documentation, log output, meeting notes, long git diffs, error traces.
local_transform
Perform mechanical code transformations locally. These are pattern-based transforms that don't require architectural understanding - the kind of work that burns API tokens for no good reason. Use this for: converting between formats, renaming patterns, migrating syntax, generating boilerplate from examples, etc.
local_vision
Have a local vision model SEE a rendered image (screenshot of a UI) and report what is literally on screen - for zero API cost. local_analyze is TEXT-ONLY; this is the multimodal path. It REPORTS (is the main content populated or blank/error, what regions exist, any illegible/clipped text, what the eye lands on first). It does NOT rank severity, judge on-brand, or greenlight a change - a local vis

Public scan report

scanner v0.1.10 · 2026-10-16 · same rubric, same numbers if you re-run it

no findings

Code scan3 source files scanned25/25
–Live reliabilityno gateway calls yet and no remote to proben/a
–Tool poisoningtools not inspected (local package is not executed); not countedn/a
Auth qualitylocal package, no credentials required12/15
Maintenancelast push 25 days ago15/15
Maintainer identityregistry namespace matches repository owner7/10

Overall 91/100. Components that don't apply are left out of the denominator. Any critical finding is an F.Rubric Appeal a finding JSON

How ~alter mcp-ollama compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score: 91/100; higher than 85% of 48,243 servers
Tools: 10; the typical server has 7
Tools that change things: 0%; typical: 0%. Fewer write tools means less an agent can break
Downloads a week: 45; more than 35% of 12,306 servers with a package

What its tools let an agent do: 10 read

Install ~alter mcp-ollama in Claude Code, Cursor or VS Code

Runs npx -y @truealter/mcp-ollama on your machine. Read the scan report first; the gateway never runs local packages.

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

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What the publisher says

From the ~alter mcp-ollama repository's README, as published. We do not edit it. Read it on GitHub

~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.

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

~alter mcp-ollama: common questions

Is ~alter mcp-ollama MCP server safe?: Yes, by our scan: it is graded A (91/100). Read the ~alter mcp-ollama safety report
How do I install ~alter mcp-ollama?: It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does ~alter mcp-ollama need an API key?: Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is ~alter mcp-ollama maintained?: The last commit was 44 days ago (2026-09-22). The latest release is v0.2.1.
How does ~alter mcp-ollama compare with other MCP servers?: safety score 91/100 (higher than 85% of 48,243 servers); tools 10 (the typical server has 7); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.