prismAId MCP
MCP server for prismAId AI-assisted systematic reviews and protocol conformance checking.
Open source Open in the app JSON README (API)
About
MCP server for prismAId AI-assisted systematic reviews and protocol conformance checking.
Details
- Kind
- MCP servers
- Topic
- No topic detected
- Publisher
- open-and-sustainable
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 0.17.1
- Stars
- 28
- Forks
- 4
- Last push
- 2026-08-20T10:34:10Z
- Repository state
- ativo
- Language
- Go
- License
- AGPL-3.0
- Added
- 2026-08-29 04:00:58
- Updated
- 2026-08-29 04:00:58
- Origin id
io.github.open-and-sustainable/prismaid-mcp
README
#  prismAId
# Open Science AI Tools for Systematic, Protocol-Based Literature Reviews
prismAId offers a suite of tools using generative AI models to streamline systematic reviews of scientific literature.
It provides simple-to-use, efficient, and replicable methods for screening and analyzing research papers with no coding skills required.
---
[](https://github.com/Open-and-Sustainable/prismAId/releases)
[](https://go.dev/)
[](https://goreportcard.com/report/github.com/open-and-sustainable/prismaid)
[](https://pkg.go.dev/github.com/open-and-sustainable/prismaid)
[](https://pypi.org/project/prismaid/)
[](https://open-and-sustainable.r-universe.dev/prismaid)
[](https://www.gnu.org/licenses/agpl-3.0.en.html#license-text)
[](https://doi.org/10.5281/zenodo.11210796)
[](https://doi.org/10.21105/joss.07616)
[](https://raw.githubusercontent.com/open-and-sustainable/prismaid_manual/main/prismaid_manual.pdf)
---
## Toolkit Overview
prismAId offers a comprehensive set of tools for systematic literature reviews:
<div style="text-align: center;">
<img src="https://raw.githubusercontent.com/open-and-sustainable/prismaid/main/figures/tools.png" alt="Tools Overview" style="width: 600px;">
</div>
### Core Tools
1. **Screening** - Filter and tag manuscripts to identify items for exclusion
2. **Download** - Download papers from Zotero collections or from URL lists
3. **Convert** - Convert files (PDF, DOCX, HTML) to plain text for analysis
4. **Review** - Process systematic literature reviews based on TOML configurations
5. **RevAIse documentation support** - Optionally document review stages as [RevAIse](https://revaise-model.readthedocs.io/stable/) review records
### Workflow
Our tools support a comprehensive systematic review workflow following the standard sequence: Search → Screen → Download → Convert → Review. RevAIse support can document Zotero download, screening, and review/extraction stages in one cumulative review record.
<div style="text-align: center;">
<img src="https://raw.githubusercontent.com/open-and-sustainable/prismaid/main/figures/prismAId_workflow.png" alt="Workflow Diagram" style="width: 600px;">
</div>
### Access Methods
- **AI agents via the MCP server** - A main entry point: connect an AI assistant to the [prismAId MCP server](https://prismaid.review/mcp-server.html) and drive every tool in conversation
- **Command Line Interface** - For users who prefer terminal-based workflows
- **Web Initializer** - A browser-based setup tool for configuring reviews
- **Programming Libraries** - API access through multiple languages:
- Go (native implementation)
- Python package
- R package
- Julia package
---
## Specifications
- **Review protocol**: Supports any literature review protocol with a preference for [PRISMA 2020](https://www.prisma-statement.org/prisma-2020), which inspired our project name.
- **Review documentation**: Optional [RevAIse](https://revaise-model.readthedocs.io/stable/) review-record support with cumulative updates and automatic backups; see the [RevAIse integration guide](https://prismaid.review/review/revaise-integration.html).
- **Protocol conformance**: Check RevAIse review records against reporting protocols such as PRISMA 2020, and get a protocol's full requirement checklist, using the SHACL shapes published by RevAIse; see the [conformance](https://prismaid.review/conformance.html) and [guidance](https://prismaid.review/guidance.html) docs.
- **Distribution**: Available as:
- Go [package](https://pkg.go.dev/github.com/open-and-sustainable/prismaid)
- Python [package](https://pypi.org/project/prismaid/)
- R [package](https://open-and-sustainable.r-universe.dev/prismaid)
- Julia [package](https://github.com/JuliaRegistries/General/tree/master/P/PrismAId)
- 'no-coding' [binaries](https://github.com/open-and-sustainable/prismaid/releases) for Windows, MacOS, and Linux (AMD64/ARM64)
- **Supported LLMs**:
1. **OpenAI**: GPT-3.5 Turbo, GPT-4 Turbo, GPT-4o, GPT-4o Mini, GPT-4.1, GPT-4.1 Mini, GPT-4.1 Nano, GPT-5, GPT-5.1, GPT-5.2, GPT-5 Mini, GPT-5 Nano, o1, o1 Mini, o3, o3 Mini, and o4 Mini
2. **GoogleAI**: Gemini 1.5 Pro, Gemini 1.5 Flash, Gemini 2.0 Flash, Gemini 2.0 Flash Lite, Gemini 2.5 Pro, Gemini 2.5 Flash, Gemini 2.5 Flash Lite, Gemini 3 Pro Preview, and Gemini 3 Flash Preview
3. **Cohere**: Command, Command Light, Command R, Command R+, Command R7B, Command R (August 2024), Command A, and Command A Reasoning
4. **Anthropic**: Claude 3 Sonnet, Claude 3 Opus, Claude 3 Haiku, Claude 3.5 Haiku, Claude 3.5 Sonnet, Claude 3.7 Sonnet, Claude 4.0 Sonnet, Claude 4.0 Opus, Claude 4.5 Opus, Claude 4.5 Sonnet, and Claude 4.5 Haiku
5. **DeepSeek**: DeepSeek Chat v3, and DeepSeek Reasoner v3
6. **Perplexity**: Sonar, Sonar Pro, Sonar Reasoning Pro, and Sonar Deep Research
7. **Cloud Providers**: AWS Bedrock, Azure AI, Vertex AI
8. **Self-Hosted**: OpenAI-compatible endpoints
- **Screening capabilities**: Deduplication, language filtering, article type classification, and off-topic detection
- **Output format**: Data in CSV or JSON formats
- **Performance**: Efficiently processes extensive datasets with minimal setup and **no coding** required
- **Programming Language**: Core implementation in Go with bindings for Python, R, and Julia
---
## Documentation
All information on installation, usage, and development is available at [prismaid.review](https://prismaid.review/) and in the [prismAId User Manual](https://raw.githubusercontent.com/open-and-sustainable/prismaid_manual/main/prismaid_manual.pdf).
---
## Credits
### Authors
Riccardo Boero - ribo@nilu.no
### Acknowledgments
This project was initiated with the generous support of a SIS internal project from [NILU](https://nilu.com). Their support was crucial in starting this research and development effort. Further, acknowledgment is due for the research credits received from the [OpenAI Researcher Access Program](https://grants.openai.com/prog/openai_researcher_access_program/) and the [Cohere For AI Research Grant Program](https://share.hsforms.com/1aF5ZiZDYQqCOd8JSzhUBJQch5vw?ref=txt.cohere.com), both of which have significantly contributed to the advancement of this work.
---
## License
GNU AFFERO GENERAL PUBLIC LICENSE, Version 3
[](https://www.gnu.org/licenses/agpl-3.0.en.html#license-text)
---
## Contributing
Contributions are welcome! Please follow guidelines at [https://github.com/open-and-sustainable/prismaid?tab=contributing-ov-file](https://github.com/open-and-sustainable/prismaid?tab=contributing-ov-file).
---
## Citation
Boero, R. (2024). prismAId - Open Science AI Tools for Systematic, Protocol-Based Literature Reviews. Zenodo. [DOI: 10.5281/zenodo.11210796](https://doi.org/10.5281/zenodo.11210796)