MCP server for Marketing
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Extract top SEO keywords from marketing copy using term frequency. Returns: {keywords: [{word, score}], total_words}
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Extract top SEO keywords from marketing copy using term frequency. Returns: {keywords: [{word, score}], total_words}
| Argument | Type | Description |
|---|---|---|
| text* | string | |
| top_n |
| integer |
{
"type": "object",
"title": "analyze_seo_keywordsArguments",
"required": [
"text"
],
"properties": {
"text": {
"type": "string",
"title": "Text"
},
"top_n": {
"type": "integer",
"title": "Top N",
"default": 15
}
}
}Fetch a page and extract HTML meta tags (title, description, og:*). Returns: {title, description, og_title, og_description, meta: {name: content}}
| Argument | Type | Description |
|---|---|---|
| url* | string |
{
"type": "object",
"title": "extract_meta_tagsArguments",
"required": [
"url"
],
"properties": {
"url": {
"type": "string",
"title": "Url"
}
}
}Server health check.
No arguments.
{
"type": "object",
"title": "health_checkArguments",
"properties": {}
}Count word frequencies in text for content/marketing analysis. Returns: {words: [{word, count, pct}], total}
| Argument | Type | Description |
|---|---|---|
| text* | string | |
| top_n | integer |
{
"type": "object",
"title": "word_frequencyArguments",
"required": [
"text"
],
"properties": {
"text": {
"type": "string",
"title": "Text"
},
"top_n": {
"type": "integer",
"title": "Top N",
"default": 20
}
}
}