Generate and evaluate academic diagrams and plots with independent model connections.
io.github.mituan-ai/paperbanana-cn MCP Server
Generate and evaluate academic diagrams and plots with independent model connections. The server is designed as an MCP toolset for producing methodology figures and visualizations from research text and data inputs, with support for bilingual content and a Gradio-based interface.
🛠️ Key Features
Generate methodology diagrams from research descriptions
Generate statistical plots from CSV or JSON data
Evaluate generated academic diagrams and plots
Uses independent model connections
Bilingual support (English and 简体中文)
🚀 Use Cases
Create academic figures for research documentation
Turn CSV or JSON datasets into statistical plots
Produce methodology diagrams from written research descriptions
Support bilingual workflows for figure creation
⚡ Developer Benefits
Tool availability: 11 tools
Compatible with scientific-visualization pipelines using CSV/JSON
Designed for Python-based development environments
Exposes MCP functionality alongside a Gradio UI
⚠️ Limitations
Limited information available about evaluation method specifics and figure formats in the provided excerpt.
PaperBanana-CN generates methodology diagrams from research descriptions and statistical plots
from CSV or JSON data. It uses the PaperBanana scientific workflow and adds separate VLM and
image-service connections, a Chinese Studio interface, and explicit aspect-ratio and resolution
controls.
One run from input to figure
The recording follows a methodology-diagram run from submitted inputs to the completed result.
Before you start
You need Python 3.10-3.12, uv, and a desktop browser.
Task
Required model connections
Methodology diagram
VLM and image generation
Statistical plot
VLM only
Multi-panel composition and run browsing
None
Each connection specifies its own protocol, Base URL, API key, model name, and timeout. The VLM and
image roles may use the same service or two different services.
Quick start
1. Launch Studio
bash
uvx paperbanana-cn studio
Open http://127.0.0.1:7860. uvx runs the package in an isolated environment and does not modify
Debian or Ubuntu's system Python.
2. Add the model connections
Open Settings → VLM connection, fill in the service fields, and select Save and use. Repeat
under Image connection before generating a methodology diagram.
Editing a saved connection does not activate it. An empty API-key field keeps the stored key.
Studio does not fill stored keys back into the browser.
Connection manager screenshot and protocol notes
The connection guide
lists the supported protocols, credential storage rules, connection tests, and legacy mode.
3. Generate a figure
Open Methodology diagram, provide the method content and figure caption, then choose an aspect
ratio, resolution, and output format.
The two model roles have independent protocol, Base URL, API key, model, and timeout settings.
Studio, CLI, and MCP resolve the same saved connections. Saved profiles contain credential
references; API keys remain outside the repository and run metadata.
Official APIs, OpenAI-compatible services, and Gemini-compatible services are supported. Provider
specifics stay in the adapters rather than the scientific workflow.
Chinese and English Studio
The Studio interface, help text, validation, progress messages, and errors are available in Chinese
and English. Changing the interface language does not rewrite prompts, paper text, or labels inside
the generated figure.
Studio shows the request size or provider-native tier before generation. If an adapter cannot
produce the selected combination, validation stops the request and reports the unsupported option.
Studio workflows
Area
Workflow
Model connections
Create
Methodology diagram
VLM and image
Create
Statistical plot
VLM
Improve
Continue a saved run
Depends on the saved run
Improve
Quality evaluation
VLM
Automate
Full-paper orchestration
VLM and image
Automate
Batch generation
Depends on the task type
Automate
Parameter sweep
VLM and image
Tools
Multi-panel composition
None
Tools
Run browser
None
Methodology-diagram workspace
Statistical-plot workspace using synthetic demonstration data
The scientific figure-generation core is based on
llmsresearch/paperbanana. PaperBanana-CN is an
unofficial community implementation and is not affiliated with or endorsed by the upstream
authors.