PaperBanana-CN
Generate and evaluate academic diagrams and plots with independent model connections.
Connector by mituan-ai · GitHub account verified by the MCP Registry
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Permissions
What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.
- Tools
- 3 read · 4 write · 0 delete · 4 not yet classified
- Secrets
- None asked for
- Install scripts
- Not scanned yet
- Runs as
- Python package
Tools by what they do 11
Read from the source code; the running server may list different tools.
Read 3 · Look things up without changing anything.
evaluate_diagramevaluate_plotorchestrate_figures
Write 4 · Create, change, send or run things.
batch_diagramsbatch_plotscontinue_rundownload_references
Not yet classified 4 · We could not tell from the name and description.
continue_diagramcontinue_plotgenerate_diagramgenerate_plot
Tools (11)
Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].
batch_diagramsRun methodology diagram batch from a manifest (YAML or JSON). Each manifest item needs ``input`` (text or PDF path) and ``caption``. Paths are resolved relative to the manifest file directory. Returns JSON with ``batch_dir``, ``batch_report_path``, per-item summary, ``composite_path`` when configured, and ``strict_success`` (false if any item failed).
batch_plotsRun statistical plot batch from a manifest (YAML or JSON). Each item needs ``data`` (CSV or JSON path) and ``intent``. When ``vlm_provider`` is omitted, defaults to ``gemini`` (same as CLI plot-batch). Returns JSON with ``batch_dir``, ``batch_report_path``, item summary, and ``strict_success``.
continue_diagramContinue a methodology diagram run under ``output_dir`` / ``run_id``. Loads ``run_input.json`` and the latest iteration from an existing ``run_*`` directory (same as ``paperbanana-cn generate --continue-run``). Runs more visualizer–critic rounds without redoing retrieval / planner / stylist. Args: run_id: Directory name (e.g. ``run_20250109_120000_abc``). output_dir: Base output directory containing the run folder. feedback: Optional notes for the critic (same as CLI ``--feedback``). iterations: Extra refinement rounds when ``auto_refine`` is false; also sets ``refine…
continue_plotContinue a statistical-plot run (same contract as ``continue_diagram``). Use when ``run_input.json`` has ``diagram_type`` ``statistical_plot``.
continue_runContinue refinement for a previous diagram or plot run (CLI: ``generate --continue-run``). Loads state from ``<output_dir>/<run_id>/`` (default ``outputs/`` from settings), then runs additional visualizer/critic iterations in the same run directory. Optional ``feedback`` is passed to the critic, matching ``--feedback`` on the CLI. Args: run_id: Directory name of the run (e.g. ``run_20260218_125448_e7b876`` under ``outputs/``). feedback: Optional user notes for the critic (layout, labels, style). iterations: Extra refinement iterations when ``auto_refine`` is False (default 3). …
download_referencesDownload the PaperBananaBench reference set. Downloads ~254 MB of reference diagrams (~298 examples) from the project-hosted GitHub release mirror (SHA256-verified) and caches them locally. The Retriever agent uses these for better in-context learning during diagram generation. Only needs to be run once — subsequent calls detect the cached data and return immediately. Use force=True to re-download. Args: force: Re-download even if already cached. Returns: Status message with cache location and example count.
evaluate_diagramEvaluate a generated diagram against a human reference on 4 dimensions. Compares the model-generated image to a human-drawn reference using Faithfulness, Conciseness, Readability, and Aesthetics scoring with hierarchical aggregation. Args: generated_path: File path to the model-generated image. reference_path: File path to the human-drawn reference image. context: Original methodology text used to generate the diagram. caption: Figure caption describing what the diagram communicates. Returns: Formatted evaluation scores with per-dimension results and overall winner.
evaluate_plotEvaluate a generated statistical plot against a human reference on 4 dimensions. Args: generated_path: File path to the model-generated plot. reference_path: File path to the human reference plot. data_json: JSON string containing the source data used to generate the plot. intent: Communicative intent used for plot generation. Returns: Formatted evaluation scores with per-dimension results and overall winner.
generate_diagramGenerate a publication-quality methodology diagram from text. Args: source_context: Methodology section text or relevant paper excerpt. caption: Figure caption describing what the diagram should communicate. iterations: Number of refinement iterations (default 3, used when auto_refine=False). aspect_ratio: Target aspect ratio. Supported: 1:1, 4:3, 3:2, 5:4, 16:9, 21:9, 4:5, 3:4, 2:3, 9:16. optimize: Enrich context and sharpen caption before generation (default True). Set False to skip preprocessing for faster results. auto_refine: Let critic loop until …
generate_plotGenerate a publication-quality statistical plot from JSON data. Args: data_json: JSON string containing the data to plot. Example: '{"x": [1,2,3], "y": [4,5,6], "labels": ["a","b","c"]}' intent: Description of the desired plot (e.g. "Bar chart comparing model accuracy"). iterations: Number of refinement iterations (default 3, used when auto_refine=False). aspect_ratio: Target aspect ratio. Supported: 1:1, 4:3, 3:2, 5:4, 16:9, 21:9, 4:5, 3:4, 2:3, 9:16. optimize: Enrich context and sharpen caption before generation (default True). Set False to skip p…
orchestrate_figuresPlan and optionally generate a multi-figure publication package from a paper. Mirrors ``paperbanana-cn orchestrate``. Use ``dry_run=True`` to write ``orchestration_plan.json`` only (no API generation). For continuation, pass ``resume_orchestrate`` with an orchestration id or package directory path. Returns: JSON string with orchestration_id, paths to ``figure_package.json``, ``figures.tex``, ``captions.md``, ``orchestration_plan.json``, counts, ``strict_success``, and ``failures`` when applicable.
Signals
- Stars
- 84
- Forks
- 5
- Open issues
- 0
- Contributors
- 36
- Weekly downloads
- 19
- Last commit
- Jul 24, 2026 (3 months ago)
- Last release
- Jul 24, 2026 (3 months ago)
- Last package publish
- Jul 24, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026) and the package registry.
Details
- Registry name
io.github.mituan-ai/paperbanana-cn- Version
- 2.0.1
- Auth
- No auth
- Packages
- pypi paperbanana-cn
- License
- MIT
- Repository
- github.com/mituan-ai/PaperBanana-CN
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
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PaperBanana-CN MCP server. Agent Mart. https://agentmart.dev/connectors/mituan-ai-paperbanana-cn (last updated 2026-10-24)