Drive EViews from Python, and expose it to LLM clients over MCP
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# eviews-mcp [](https://github.com/merwanroudane/MCP_EVIEWS/actions/workflows/tests.yml) [](https://pypi.org/project/eviews-mcp/) [](https://pypi.org/project/eviews-mcp/) [](LICENSE) [](https://pypi.org/project/eviews-mcp/) [](https://www.eviews.com) Drive **EViews** from Python, and expose it to LLM clients over the Model Context Protocol. **[Documentation site](https://merwanroudane.github.io/MCP_EVIEWS/)** · **[Researcher guide](https://github.com/merwanroudane/MCP_EVIEWS/blob/main/docs/EViews-Researcher-Guide.md)** · **[PyPI](https://pypi.org/project/eviews-mcp/)** Two things in one package: - **A library.** An `EViews` class for scripts and notebooks — build workfiles, estimate models, read results back as text or pandas DataFrames. - **An MCP server.** The same capabilities as tools, so an assistant can do econometrics in a real EViews session. Built and tested against **EViews 13** on Windows; EViews 10–14 resolve correctly through the same COM interface. > **New to this?** The [**EViews Researcher Guide**](https://github.com/merwanroudane/MCP_EVIEWS/blob/main/docs/EViews-Researcher-Guide.md) > takes you from a clean machine to a finished ARDL study, with every command and > every output verified against a real EViews session. No Python knowledge assumed. ## Install ```bash pip install eviews-mcp ``` With pandas support: ```bash pip install "eviews-mcp[pandas]" ``` Or from a clone, for development: ```bash git clone https://github.com/merwanroudane/MCP_EVIEWS.git cd MCP_EVIEWS pip install -e .[dev] ``` R…
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