~alter mcp-ollama

Install

Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/true-alter-mcp-ollama

About

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools

4 read · 1 write · 0 delete · 5 not yet classified

Secrets

None asked for

Install scripts

Not scanned yet

Runs as

Node.js package

Tools (10)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

• 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 zero API cost. Accepts up to ~12K tokens of code context (16K model context minus overhead). For larger contexts, break into focused chunks (one function, one class).

• 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 GPU.

• 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 vision model reads pixels well but ranks badly, so keep the judgment on the calling model. Modes: 'see' (full structural report), 'emptystate' (populated-vs-degraded data check), 'legibility' (readabil…

Signals

Stars

0

Forks

0

Open issues

0

Last commit

Sep 22, 2026 (1 month ago)

Last release

Sep 3, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

Registry name

io.github.true-alter/mcp-ollama

Version

0.2.1

Auth

No auth

Packages

npm @truealter/mcp-ollama

License

Apache-2.0

Repository

github.com/true-alter/mcp-ollama

Website

github.com/true-alter/mcp-ollama#readme

First seen

Oct 24, 2026

Last checked

Oct 24, 2026

Source

Official MCP Registrygithub-graphql