# I wrapped Google TimesFM-3 as an MCP server — you still cannot use the weights in production

> Source: <https://dev.to/thenameisdevair/i-wrapped-google-timesfm-3-as-an-mcp-server-you-still-cannot-use-the-weights-in-production-4inp>
> Published: 2026-09-02 06:34:11+00:00

Google released TimesFM-3 on 31 August 2026. I shipped an MCP server for it the next day so Claude Desktop, Claude Code, and Cursor can call the model as a tool.

Repo: [https://github.com/thenameisdevair/timesfm3-mcp](https://github.com/thenameisdevair/timesfm3-mcp)

The tool is `forecast(history, horizon)`

.

You pass a chronological list of numbers. You get:

`forecast`

— median / point prediction`quantiles`

— the nine official TimesFM-3 heads, `q10`

through `q90`

TimesFM-3 already produced those quantile heads. Most thin wrappers throw them away. This one does not.

| Piece | License |
|---|---|
| This MCP wrapper | Apache-2.0 |
TimesFM-3 weights (`google/timesfm-3.0-pytorch` ) |
non-commercial, non-production |

You can research, evaluate, and run agent experiments. You cannot put this checkpoint behind a paid API, a customer deliverable, or a live demand planner. Google’s commercial path is BigQuery / AlloyDB `AI.FORECAST`

.

If a README hides that, it is not a serious integration.

Weights are gated on Hugging Face. Accept the model terms first.

```
git clone https://github.com/thenameisdevair/timesfm3-mcp.git
cd timesfm3-mcp
python3 -m venv venv
source venv/bin/activate
pip install -r local/requirements.txt
pip install git+https://github.com/google-research/timesfm.git
huggingface-cli login
cd local && python client.py
```

Point Claude or Cursor at local/server.py using the venv Python. Config snippets are in the README.

No multivariate targets yet. No past/future covariates. No commercial backend. Those are next. This cut exists so “TimesFM-3 MCP” has a public, honest surface while the launch is still warm.

If the tool shape is wrong for your agent, feel free to open an issue on the repo.