Install
$ agentstack add mcp-mituan-ai-paperbanana-cn ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
English · 简体中文
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
uvx paperbanana-cn studio
Open . 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 same task from the CLI:
paperbanana-cn generate \
--input method.txt \
--caption "Overview of the proposed architecture" \
--aspect-ratio 16:9 \
--resolution 2K \
--format png
What PaperBanana-CN adds
Separate VLM and image connections
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.
Aspect ratios and resolution
Supported aspect ratios:
1:1 · 4:3 · 3:2 · 5:4 · 16:9 · 21:9 · 4:5 · 3:4 · 2:3 · 9:16
Resolution tiers:
1K · 2K · 4K
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
CLI, MCP, Docker, and Colab
| Entry point | Command or link | |---|---| | Studio | paperbanana-cn studio | | CLI | paperbanana-cn generate --help | | MCP server | paperbanana-cn mcp | | GitHub Action | Action reference | | Docker | ghcr.io/mituan-ai/paperbanana-cn:2.0.1 | | Colab | Quickstart notebook |
MCP client configuration
{
"mcpServers": {
"paperbanana-cn": {
"command": "uvx",
"args": ["paperbanana-cn", "mcp"]
}
}
}
The server provides 11 tools and reads the same active connections as Studio and CLI. See the MCP guide for the tool list and arguments.
Docker
docker run --rm -p 7860:7860 \
-v paperbanana-cn-config:/home/paperbanana/.config/paperbanana-cn \
-v paperbanana-cn-data:/home/paperbanana/.local/share/paperbanana-cn \
-v paperbanana-cn-outputs:/work/outputs \
ghcr.io/mituan-ai/paperbanana-cn:2.0.1 \
studio --host 0.0.0.0
Permanent install, source setup, and optional providers
Install the command in a uv-managed environment:
uv tool install paperbanana-cn
paperbanana-cn studio
Run the current source checkout:
git clone https://github.com/mituan-ai/PaperBanana-CN.git
cd PaperBanana-CN
uv sync
uv run paperbanana-cn studio
The default package includes Studio, MCP, PDF input, OpenAI-compatible services, and Gemini.
| Optional adapter | Install | |---|---| | AWS Bedrock | uv tool install "paperbanana-cn[bedrock]" | | Anthropic | uv tool install "paperbanana-cn[anthropic]" | | LiteLLM | uv tool install "paperbanana-cn[litellm]" | | All optional providers | uv tool install "paperbanana-cn[all-providers]" |
For CI, use paperbanana-cn connections add --api-key-env ENV_VAR so the key is read from an environment variable instead of a command-line value.
V1 and upstream
V2 is maintained on main as the paperbanana-cn distribution, the paperbanana_cn Python module, and the paperbanana-cn command.
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.
Community
PaperBanana-CN is maintained by mituan under the MIT License.
- Ask usage questions in Discussions.
- Report reproducible bugs in Issues.
- Report vulnerabilities through Private Vulnerability Reporting.
- Read CONTRIBUTING.md before opening a pull request.
Development checks
git clone https://github.com/mituan-ai/PaperBanana-CN.git
cd PaperBanana-CN
uv sync --extra dev
uv run pytest tests/ -q
uv run ruff check paperbanana_cn/ mcp_server/ tests/ scripts/
Do not upload API keys, private relay URLs, unpublished papers, private datasets, local connection stores, or generated run directories.
Star history
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: mituan-ai
- Source: mituan-ai/PaperBanana-CN
- License: MIT
- Homepage: https://github.com/mituan-ai/PaperBanana-CN
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.