claude-ollama-mcp

claude-ollama-mcp

Lets Claude query and manage a local Ollama server — list models, inspect them, run generate/chat completions, pull or delete models.

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访问服务器

README

Claude Ollama

Lets Claude Desktop query and manage a local Ollama server. List installed models, inspect them, run one-shot generate/chat completions against any local model, or pull/delete models from the registry — all without opening a terminal.

Typical use: comparing Claude's answer to a local model on the same prompt, running cheap bulk completions against a quantized model, or checking custom training-checkpoint models you've imported into Ollama.

Requirements

  • A running Ollama server (ollama serve or the Ollama app).
  • Default endpoint is http://localhost:11434. Override via the ollama_url user config in Claude Desktop's extension settings if you run Ollama on a different host or port.
  • No npm dependencies — pure Node over the HTTP API.

Install (Claude Desktop)

  1. Download the latest Ollama.mcpb from the Releases page.
  2. In Claude Desktop: Settings → Extensions → Extension Developer → Install Extension → pick the .mcpb.
  3. (Optional) In the extension's settings, set Ollama server URL if you run Ollama on a non-default host/port. Leave blank for http://localhost:11434.

Tools

Tool Annotation Purpose
ollama_status read-only Health check + server version
list_models read-only Local models with size, digest, family, parameter size, quantization
list_running read-only Models currently loaded in VRAM
show_model read-only Model details: modelfile, parameters, template, capabilities
generate open-world One-shot text completion (non-streaming)
chat open-world Chat completion with message history (non-streaming)
pull_model open-world Download a model from the registry
delete_model destructive Remove a locally-installed model

Example prompts

"Which local models do I have installed, and which one is currently loaded in VRAM?"

"Run forge:b6c1 on this prompt: '<blah>'. Compare that output to your own answer."

"Show me the modelfile for forge:b7c1 — I want to check the temperature setting."

"Pull llama3.1:70b." (expect a long wait for large models)

"Delete the forge:b5c3 model — I don't need that checkpoint anymore."

Privacy policy

This extension runs entirely on your local machine and sends HTTP requests only to your Ollama server (default http://localhost:11434). No data leaves your machine unless you explicitly configure ollama_url to point at a remote Ollama instance, in which case the prompts and responses travel to that server.

The information visible to Claude includes:

  • All prompts and chat messages you pass to generate and chat (these go to the Ollama server, which may log them depending on its configuration).
  • Full text of completions returned by Ollama.
  • Metadata for every installed model (names, digests, sizes, quantization, modelfile contents).
  • Which models are currently loaded in VRAM and their size footprint.

If you have installed models containing proprietary fine-tunes or modelfiles with sensitive metadata, note that Claude will see that information when you call show_model or list_models.

delete_model is destructive and cannot be undone from this extension — the model must be re-pulled from the registry (or re-imported from source blobs) if deleted by mistake.

Troubleshooting

"cannot reach Ollama at http://localhost:11434 — is the server running?" — Start Ollama with ollama serve or launch the Ollama app. Verify with curl http://localhost:11434/ (should return "Ollama is running").

pull_model hangs for a long time — Ollama's pull API with stream: false blocks until the full download completes, which for multi-GB models can take many minutes. If you're pulling a huge model, run ollama pull <name> in a terminal instead — you'll see streaming progress there, and subsequent MCP calls will find the model already installed.

Custom/remote Ollama endpoint — Set ollama_url in the extension's settings (e.g. http://192.168.1.42:11434). Requires restart of the extension.

list_running shows a model after you stopped using it — Ollama keeps models hot in VRAM for a configurable TTL (default 5 minutes). The expires_at timestamp tells you when it'll unload. This is Ollama's behavior, not the extension's.

Development

Single ~400-line Node.js script, zero npm dependencies. Rebuild the .mcpb:

cd bundle-source
zip -j ../Ollama.mcpb manifest.json package.json server.js README.md LICENSE icon.png glama.json

License

MIT. See LICENSE.

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