search_cortex_api_docs
Search Cortex Cloud API documentation to find specific information, endpoints, or usage examples for development needs.
Instructions
Search Cortex Cloud API documentation
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Implementation Reference
- server.py:197-201 (handler)MCP tool handler for 'search_cortex_api_docs'. Registers the tool and implements the logic by calling indexer.search_docs with site='cortex_api' and returning JSON-formatted results.
@mcp.tool() async def search_cortex_api_docs(query: str) -> str: """Search Cortex Cloud API documentation""" results = await indexer.search_docs(query, site='cortex_api') return json.dumps(results, indent=2) - src/main.py:197-201 (handler)MCP tool handler for 'search_cortex_api_docs'. Registers the tool and implements the logic by calling indexer.search_docs with site='cortex_api' and returning JSON-formatted results.
@mcp.tool() async def search_cortex_api_docs(query: str) -> str: """Search Cortex Cloud API documentation""" results = await indexer.search_docs(query, site='cortex_api') return json.dumps(results, indent=2) - server.py:104-155 (helper)Core helper method in DocumentationIndexer class that implements the document search logic, including relevance scoring, snippet extraction, and result sorting. This is the primary implementation delegated to by the tool 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] - server.py:13-24 (helper)Dataclass used to cache indexed documentation pages, including expiration logic.
@dataclass class CachedPage: title: str content: str url: str site: str timestamp: float ttl: float = 3600 # 1 hour default TTL @property def is_expired(self) -> bool: return time.time() > self.timestamp + self.ttl