search_prisma_docs
Search the Prisma Cloud documentation to find relevant information by entering a query. Retrieve answers directly from the official Prisma Cloud docs for quick reference.
Instructions
Search Prisma Cloud documentation
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Input Schema (JSON Schema)
{
"properties": {
"query": {
"title": "Query",
"type": "string"
}
},
"required": [
"query"
],
"title": "search_prisma_docsArguments",
"type": "object"
}
Implementation Reference
- src/main.py:195-199 (handler)The handler function for the search_prisma_docs tool, registered via @mcp.tool() decorator. It invokes the DocumentationIndexer.search_docs method for Prisma Cloud site and returns JSON results.@mcp.tool() async def search_prisma_docs(query: str) -> str: """Search Prisma Cloud documentation""" results = await indexer.search_docs(query, site='prisma_cloud') return json.dumps(results, indent=2)
- server.py:191-195 (handler)Duplicate handler function for the search_prisma_docs tool in server.py file.@mcp.tool() async def search_prisma_docs(query: str) -> str: """Search Prisma Cloud documentation""" results = await indexer.search_docs(query, site='prisma_cloud') return json.dumps(results, indent=2)
- src/main.py:108-160 (helper)Core helper method in DocumentationIndexer class that performs relevance-based search across cached documentation pages, used by the search_prisma_docs handler.async def search_docs(self, query: str, site: str = None) -> List[Dict]: """Search indexed documentation""" if not self.cached_pages: return [] query_lower = query.lower() results = [] for url, page in self.cached_pages.items(): # Filter by site if specified if site and page.site != site: continue # Calculate relevance score score = 0 title_lower = page.title.lower() content_lower = page.content.lower() # Higher score for title matches if query_lower in title_lower: score += 10 # Even higher for exact title matches if query_lower == title_lower: score += 20 # Score for content matches content_matches = content_lower.count(query_lower) score += content_matches * 2 # Score for partial word matches in title query_words = query_lower.split() for word in query_words: if word in title_lower: score += 5 if word in content_lower: score += 1 if score > 0: # Extract snippet around first match snippet = self._extract_snippet(page.content, query, max_length=200) results.append({ 'title': page.title, 'url': page.url, 'site': page.site, 'snippet': snippet, 'score': score }) # Sort by relevance score (highest first) and limit results results.sort(key=lambda x: x['score'], reverse=True) return results[:10]
- src/main.py:195-195 (registration)MCP tool registration decorator for search_prisma_docs.@mcp.tool()
- server.py:191-191 (registration)MCP tool registration decorator for search_prisma_docs in server.py.@mcp.tool()