genpark-multimodal-chart-data-point-extractor-skill
OfficialClick on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@genpark-multimodal-chart-data-point-extractor-skillextract the data points from this line chart into a table"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
genpark-chart-coordinates
Calibrate linear chart axes and convert supplied bar or scatter pixel coordinates to values. No image recognition or logarithmic axes.
Python 3.9+; standard library runtime; MIT license.
Install and run
Download genpark-chart-coordinates.mcpb from GitHub Releases and install with an MCPB-compatible client. Python must be installed and available as python.
Alternatively clone this repository and configure an MCP stdio server with command python and arguments containing the absolute path to mcp_server.py.
Related MCP server: genpark-visual-grounding-spec-comparison-skill
Tools
calibrate_axis_scaleextract_bar_chart_seriesextract_scatter_pointsrun_benchmark_chart_extraction
Run python -m unittest discover -s tests for regression checks. The official MCP SDK integration check uses the development dependency mcp: python tests/check_mcp.py.
Limitations
These are deterministic helpers operating on supplied structured data, not machine-learning models. Input and output remain in the local process. No hosted endpoint, automatic file access or network access is required. State lasts only for the current process. Benchmark tools run synthetic examples in isolated state; their status is not a production-quality certification.
Bar outputs are axis values at their tops, not differences from the baseline. Supply slope/intercept calibration results; linear axes only.
This server cannot be deployed
Maintenance
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