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Ollama Handoff logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 2:16:01 PM

Ollama Handoff

User RatingsBe the first to rate and review this MCP server!
View Repository3 GitHub StarsTotal stargazers on GitHub for the source repository (3 stars).Visit Website
ollamalocal-modelcode-reviewsummarizationcommit-message

MCP server routing routine NLP tasks to a local Ollama model to save cloud LLM costs and context.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "michael-whitecapdata-ollama-handoff": {
      "command": "uvx",
      "args": [
        "ollama-handoff"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (8) Directory Badge Claim listing Alternatives๐Ÿ’ป More in Developer Tools

Overview

This MCP server exposes a local Ollama model as specialized tools for tasks like summarization, code review, extraction, and drafting commit messages. It enables AI agents to offload inexpensive or repetitive work from costly cloud LLMs to a local GPU, reducing cloud usage and preserving context budget. Each tool includes baked-in system prompts tailored for its task, allowing agents to hand off work efficiently without restating instructions. Use it when you want to optimize cloud LLM usage by delegating routine tasks to a local model.

Use cases

โ€ขSummarize long logs, transcripts, or documents locally
โ€ขGenerate conventional commit messages from code diffs
โ€ขPerform quick first-pass code reviews on diffs
โ€ขExtract structured data like URLs or TODOs from text
โ€ขConduct multi-turn local chat sessions for context-dependent tasks

Key features

โ€ขOne-shot and multi-turn local prompt tools
โ€ขStructured summaries with headlines and bullet points
โ€ขConventional commit message drafting from diffs
โ€ขQuick first-pass code review of diffs
โ€ขListing of locally available Ollama models
โ€ขConfigurable via environment variables for model and server settings

Capabilities & Tool Schemas (8) ~99 tokensApproximate context cost of this serverโ€™s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server โ€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Ollama Handoff.

ask_local

One-shot prompt to the local model

chat_local

Multi-turn local chat

summarize_local

Structured summary (headline + bullets)

code_review_local

Quick first-pass review of a diff/code

draft_commit_message_local

Conventional commit message from a diff

extract_local

Pull structured items from unstructured text

Documentation Overview

ollama-handoff

An MCP server that offloads cheap work from your cloud LLM agent to a local Ollama model.

CI PyPI Python MCP License: MIT

Your frontier model (Claude, GPT, etc.) is brilliant and metered. A lot of the work it gets handed โ€” summarizing a log, drafting a commit message, pulling every URL out of a file, a quick first-pass code review โ€” doesn't need frontier reasoning at all. ollama-handoff exposes your local Ollama instance as a handful of purpose-built MCP tools, so your agent can route that work to a model on your own GPU โ€” at zero cloud cost โ€” and spend its (paid) reasoning budget on the things that actually need it.

This isn't a generic "wrap the Ollama API" server. Each tool ships with a baked-in system prompt and a description written for the calling agent, so the agent knows when to hand off and gets a tuned result back without re-stating instructions every call.


Why you'd want this

  • ๐Ÿ’ธ Spend less. Routine offloads run locally and bill nothing.
  • โšก Keep the big model focused. Summaries, extractions, and drafts don't eat its context or your budget.
  • ๐Ÿง  Tuned, not raw. summarize_local, code_review_local, draft_commit_message_local, and extract_local come with reviewer/summarizer/extractor system prompts already dialed in.
  • ๐Ÿ”Œ Drop-in. One MCP registration; works with Claude Code, Claude Desktop, Cursor, and any MCP client.
  • ๐Ÿชถ Tiny & auditable. Two dependencies (mcp, httpx), fully typed, unit-tested, no telemetry.

Requirements

  • Ollama running locally (ollama serve) with at least one model pulled, e.g. ollama pull qwen2.5-coder:14b.
  • Python 3.11+ (or just uvx, which manages it for you).

Install

The fastest path is uv โ€” no manual venv needed:

bash
uvx ollama-handoff          # run directly
# or
pip install ollama-handoff  # then run: ollama-handoff

Claude Code

Terminal
claude mcp add ollama-handoff -- uvx ollama-handoff

Claude Desktop / Cursor (mcp config block)

JSON Config
{
  "mcpServers": {
    "ollama-handoff": {
      "command": "uvx",
      "args": ["ollama-handoff"],
      "env": {
        "OLLAMA_DEFAULT_MODEL": "qwen2.5-coder:14b"
      }
    }
  }
}

Run with Docker

A Dockerfile is included. The server speaks MCP over stdio, so run it interactively (-i) and point it at your Ollama instance:

Terminal
docker build -t ollama-handoff .
docker run --rm -i -e OLLAMA_URL=http://host.docker.internal:11434 ollama-handoff

On native Linux (no Docker Desktop), use --network=host with OLLAMA_URL=http://localhost:11434.

Tools

ToolWhat it doesWhen the agent should reach for it
ask_localOne-shot prompt to the local modelAny handoff that doesn't need frontier reasoning
chat_localMulti-turn local chatHandoffs needing more than one turn of context
summarize_localStructured summary (headline + bullets)Long files, logs, transcripts, docs
code_review_localQuick first-pass review of a diff/codeCheap pre-filter before a deep review
draft_commit_message_localConventional commit message from a diffRoutine commits
extract_localPull structured items from unstructured textURLs, function names, error codes, TODOs
list_modelsList locally available Ollama modelsDiscovery / choosing a model
server_infoReport the effective configurationDebugging setup

Configuration

All configuration is via environment variables set in your MCP registration:

VariableDefaultDescription
OLLAMA_URLhttp://localhost:11434Base URL of the Ollama server
OLLAMA_DEFAULT_MODELqwen2.5-coder:14bDefault model for handoffs
OLLAMA_NUM_CTX32768Context window in tokens
OLLAMA_KEEP_ALIVE30mHow long to keep the model resident in VRAM
OLLAMA_TIMEOUT_S600Per-request timeout, seconds

Example

Once registered, you don't call the tools yourself โ€” your agent does. A typical exchange:

You: Summarize the errors in build.log and draft a commit for the staged fix.

Agent: (calls summarize_local(build.log, focus="errors and stack traces") and draft_commit_message_local(git diff --staged) โ€” both run on your GPU, nothing billed) โ†’ returns the summary + commit message.

Development

bash
git clone https://github.com/Michael-WhiteCapData/ollama-handoff
cd ollama-handoff
uv pip install -e ".[dev]"
ruff check .
pytest          # tests use httpx.MockTransport โ€” no running Ollama required

See CONTRIBUTING.md. Contributions welcome โ€” especially new specialized handoff tools.

License

MIT ยฉ Michael Tierney

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

GitHub stars
3
Stargazers on the source repository.
Last commit
2mo ago
Most recent push to the default branch.
Tools exposed
8
Callable tools this server registers over MCP.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Ollama Handoff

It uses a locally running Ollama model, which you must run with 'ollama serve' and have at least one model pulled.

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Technical Specs & Signals

Category๐Ÿ’ปDeveloper Tools
PricingFree
More technical detailsExpand โ–พ
TransportSTDIO
RuntimePython
AuthNo auth required
LicenseMIT
ClientsClaude Desktop, Cursor, Cline / VS Code
Last updatedAug 9, 2026
9/10 checks healthy over the last 32d
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars3
GitHub Star CountTotal stargazers on GitHub representing community popularity (3 stars).
Last commit2mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jun 23, 2026
55Quality signal: Good ยท 55/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools28/30
Adoption & activity3/15
Community engagement0/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 23d ago via OSV.dev ยท ollama-handoff (PyPI)

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