MCP server for evidence-based bullet point summarization guidance
npm install bullet-mcp---
MCP server for evidence-based bullet point summarization guidance. Validates and improves bullet lists using scientifically-validated principles from cognitive psychology and UX research.
- Score bullet lists (0-100) against 7 evidence-based rules
- Letter grades (A/B/C/D/F) with actionable feedback
- Research citations for each validation rule
- Context awareness (document, presentation, reference)
- Sections support for long documents with multiple chapters/topics
``bash`
npm install bullet-mcp
Or install globally:
`bash`
npm install -g bullet-mcp
Add to your Claude Desktop config (claude_desktop_config.json):
`json`
{
"mcpServers": {
"bullet": {
"command": "npx",
"args": ["bullet-mcp"]
}
}
}
Validates bullet point lists against evidence-based cognitive research.
Input:
`json`
{
"items": [
{ "text": "Use 3-7 items per list for optimal recall", "importance": "high" },
{ "text": "Place critical information first and last" },
{ "text": "Maintain parallel grammatical structure" },
{ "text": "Keep lines between 45-75 characters" },
{ "text": "Limit hierarchy to 2 levels maximum" }
],
"context": "document"
}
Output:
`json`
{
"overall_score": 97,
"grade": "A",
"summary": "Excellent bullet list following evidence-based best practices.",
"top_improvements": ["Consider adding detail or combining with a related point"],
"errors": [],
"warnings": [],
"suggestions": [...]
}
For long documents with multiple chapters or topics, use the sections format. Each section is validated separately (3-7 items per section), allowing unlimited total content.
Input:
`json`
{
"sections": [
{
"title": "Chapter 1: Introduction",
"items": [
{ "text": "Define the problem scope and context" },
{ "text": "Outline key objectives and goals" },
{ "text": "Summarize the main approach taken" }
]
},
{
"title": "Chapter 2: Methods",
"items": [
{ "text": "Describe data collection procedures" },
{ "text": "Explain analysis methodology used" },
{ "text": "Detail validation steps performed" }
],
"context": "reference"
}
],
"context": "document"
}
Output includes per-section breakdown:
`json`
{
"overall_score": 95,
"grade": "A",
"section_scores": [
{ "title": "Chapter 1: Introduction", "score": 96, "grade": "A", "item_count": 3 },
{ "title": "Chapter 2: Methods", "score": 94, "grade": "A", "item_count": 3 }
],
"summary": "Excellent structured summary across 2 sections."
}
| Rule | Threshold | Research Basis |
|------|-----------|----------------|
| List Length | 3-7 items (5 optimal) | Miller (1956), Cowan (2001): Working memory 3-4 chunks |
| Hierarchy | Max 2 levels | Kiger (1984), Nielsen: 2-level structures fastest |
| Line Length | 45-75 chars (66 optimal) | Typography research on readability |
| Serial Position | Important info first/last | Ebbinghaus (1885): U-shaped retention curve |
| Parallel Structure | Consistent grammar | Frazier et al. (1984): Faster scanning |
| First Words | Unique, scannable | Nielsen eye-tracking: First 2 words critical |
| Formatting | Consistent punctuation | Usability research |
- document (default): Optimizes for scanning and referencepresentation
- : Warns that visuals may be 43% more persuasivereference
- : Optimizes for quick lookup
| Variable | Default | Description |
|----------|---------|-------------|
| BULLET_STRICT_MODE | false | Treat warnings as errors |BULLET_NO_CITATIONS
| | false | Disable research citations in output |BULLET_NO_COLOR
| | false | Disable colored console output |
`bashInstall dependencies
npm install
Research Foundation
This tool is based on
- Working memory capacity (Miller, Cowan)
- Serial position effects (Ebbinghaus, Murdock)
- Eye-tracking studies (Nielsen Norman Group)
- Information architecture (Kiger, Zaphiris)
- Typography research (45-75 character optimal line length)
MIT