Cochrane Meta-Analysis MCP Server
Enables AI-assisted meta-analysis workflows following Cochrane methodological standards, including importing RevMan data, validation, meta-analysis, forest plots, publication bias assessment, and report generation.
README
Cochrane Meta-Analysis MCP Server
An MCP (Model Context Protocol) server that provides AI-assisted meta-analysis workflows following Cochrane methodological standards.
Features
- RevMan Import: Parse RevMan 5 (.rm5 XML) and Cochrane CSV exports
- Data Validation: Comprehensive validation against Cochrane standards
- Meta-Analysis: R-based statistical analysis using metafor/meta packages
- Forest Plots: Publication-ready visualizations
- Publication Bias: Funnel plots, Egger's test, trim-and-fill
- Reporting: Automated Cochrane-style HTML/PDF reports
Installation
npm install
npm run build
Prerequisites
- Node.js 18+
- R 4.0+ with packages:
- metafor
- meta
- ggplot2
- jsonlite
Install R packages:
install.packages(c("metafor", "meta", "ggplot2", "jsonlite"))
Configuration
Add to Claude Desktop config (~/.config/claude/claude_desktop_config.json):
{
"mcpServers": {
"cochrane-meta": {
"command": "node",
"args": ["/Users/YOUR_USERNAME/Documents/cochrane-meta-mcp/dist/index.js"]
}
}
}
Available Tools
1. import_revman_data
Import and parse RevMan 5 files or Cochrane CSV exports.
{
"file_path": "/path/to/review.rm5",
"format": "rm5"
}
2. validate_cochrane_data
Validate study data against Cochrane standards.
{
"data": { ... },
"validation_level": "comprehensive"
}
3. perform_meta_analysis
Execute meta-analysis following Cochrane Handbook Chapter 10.
{
"data": { ... },
"effect_measure": "OR",
"model": "random",
"heterogeneity_test": true
}
4. generate_forest_plot
Create publication-ready forest plot.
{
"analysis_results": { ... },
"plot_style": "classic",
"output_path": "/path/to/forest_plot.png"
}
5. assess_publication_bias
Perform publication bias assessment.
{
"analysis_results": { ... },
"methods": ["funnel_plot", "egger_test", "trim_fill"],
"output_path": "/path/to/funnel_plot.png"
}
6. generate_cochrane_report
Generate comprehensive Cochrane-style report.
{
"analysis_results": { ... },
"format": "html",
"output_path": "/path/to/report.html"
}
Example Usage with Claude
User: I have a Cochrane CSV file with 10 RCTs comparing intervention A vs control.
Can you help me run a meta-analysis?
Claude: I'll help you analyze this. First, let me import the data using the import_revman_data tool...
[Uses import_revman_data]
Claude: Great! I've imported 10 studies. Let me validate the data...
[Uses validate_cochrane_data]
Claude: Validation passed with 2 warnings about small sample sizes.
Now I'll perform the meta-analysis using a random-effects model
with odds ratios as the effect measure...
[Uses perform_meta_analysis]
Claude: The pooled OR is 0.75 (95% CI: 0.62-0.91), p=0.003, with moderate
heterogeneity (I²=45%). Let me generate a forest plot...
[Uses generate_forest_plot]
Claude: Forest plot created. Now checking for publication bias...
[Uses assess_publication_bias]
Claude: Egger's test p=0.42, no evidence of publication bias.
Generating final report...
[Uses generate_cochrane_report]
Claude: Complete! Your meta-analysis report is ready at report.html
CSV Format
For CSV imports, use this format:
study_id,authors,year,title,intervention,comparison,outcome,events_treatment,n_treatment,events_control,n_control
Study1,Smith 2020,2020,RCT of intervention,Drug A,Placebo,Mortality,10,100,20,100
Study2,Jones 2021,2021,Another RCT,Drug A,Placebo,Mortality,15,150,30,150
For continuous outcomes:
study_id,authors,year,title,intervention,comparison,outcome,mean_treatment,sd_treatment,n_treatment,mean_control,sd_control,n_control
Development
# Watch mode
npm run dev
# Build
npm run build
# Test (coming soon)
npm test
Architecture
- TypeScript MCP Server: Handles tool requests from Claude
- R Bridge: Executes statistical analyses via Rscript
- Validation Layer: Zod schemas for data validation
- Tools: Modular tool implementations for each MCP capability
Integration with Existing Tools
This MCP server integrates with your existing meta-analysis infrastructure:
- Uses your R meta-analysis scripts (
~/meta_analysis_workflow.R) - Compatible with medical research multi-agent system
- Can leverage AI citation processors for literature extraction
Cochrane Compliance
Follows:
- Cochrane Handbook for Systematic Reviews (Chapter 10)
- PRISMA reporting guidelines
- Cochrane risk of bias (RoB 2) recommendations
- GRADE framework for evidence certainty
License
MIT
Version
0.1.0
Author
Matheus Rech
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