Skip to main content
Glama
clarkemn

prisma-cloud-docs-mcp-server

index_prisma_api_docs

Index Prisma Cloud API documentation to enable search functionality. Call this tool first to prepare documentation for queries.

Instructions

Index Prisma Cloud API documentation. Call this first before searching.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_pagesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The @mcp.tool decorated handler function that implements the index_prisma_api_docs tool by invoking the DocumentationIndexer.index_site method for the 'prisma_api' site.
    @mcp.tool()
    async def index_prisma_api_docs(max_pages: int = 50) -> str:
        """Index Prisma Cloud API documentation. Call this first before searching."""
        pages_indexed = await indexer.index_site('prisma_api', max_pages)
        return f"Indexed {pages_indexed} pages from Prisma Cloud API documentation"
  • Supporting helper method in DocumentationIndexer class that performs web crawling, parsing, and caching of documentation pages from the specified site (e.g., 'prisma_api'). This is the core logic executed by the tool handler.
    async def index_site(self, site_name: str, max_pages: int = 100):
        """Index documentation from a specific site"""
        if site_name not in self.base_urls:
            raise ValueError(f"Unknown site: {site_name}")
        
        base_url = self.base_urls[site_name]
        visited_urls = set()
        urls_to_visit = [base_url]
        pages_indexed = 0
        
        async with aiohttp.ClientSession() as session:
            while urls_to_visit and pages_indexed < max_pages:
                url = urls_to_visit.pop(0)
                
                if url in visited_urls:
                    continue
                    
                visited_urls.add(url)
                
                try:
                    async with session.get(url, timeout=10) as response:
                        if response.status == 200:
                            content = await response.text()
                            soup = BeautifulSoup(content, 'html.parser')
                            
                            # Extract page content
                            title = soup.find('title')
                            title_text = title.text.strip() if title else url
                            
                            # Remove script and style elements
                            for script in soup(["script", "style"]):
                                script.decompose()
                            
                            # Get text content
                            text_content = soup.get_text()
                            lines = (line.strip() for line in text_content.splitlines())
                            chunks = (phrase.strip() for line in lines for phrase in line.split("  "))
                            text = ' '.join(chunk for chunk in chunks if chunk)
                            
                            # Store in cache
                            self.cached_pages[url] = CachedPage(
                                title=title_text,
                                content=text[:5000],  # Limit content length
                                url=url,
                                site=site_name,
                                timestamp=time.time()
                            )
                            
                            pages_indexed += 1
                            
                            # Find more links to index
                            if pages_indexed < max_pages:
                                links = soup.find_all('a', href=True)
                                for link in links:
                                    href = link['href']
                                    full_url = urljoin(url, href)
                                    
                                    # Only index URLs from the same domain
                                    if urlparse(full_url).netloc == urlparse(base_url).netloc:
                                        if full_url not in visited_urls and full_url not in urls_to_visit_set:
                                            urls_to_visit.append(full_url)
                                            urls_to_visit_set.add(full_url)
                                
                except Exception as e:
                    print(f"Error indexing {url}: {e}")
                    continue
        
        return pages_indexed
  • Dataclass used by the indexer to store cached page data with 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
  • src/main.py:219-219 (registration)
    MCP tool registration decorator for the index_prisma_api_docs function.
    @mcp.tool()
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions indexing but doesn't explain what indexing entails (e.g., data fetching, processing, storage), potential side effects, rate limits, or authentication needs. The directive to call it first hints at initialization behavior but lacks detail on outcomes or errors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with two short sentences that are front-loaded and waste no words. Every sentence serves a clear purpose: stating the action and providing usage guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (which reduces the need to describe return values) and only one parameter, the description is somewhat complete for its simplicity. However, as a tool with no annotations and a parameter lacking schema descriptions, it should provide more context on behavior and parameter meaning to be fully helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter ('max_pages') with 0% description coverage in the schema, so the description must compensate. However, the description provides no information about parameters, not even mentioning 'max_pages' or its purpose. Since there's only one parameter, the baseline is higher, but the description adds no value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Index Prisma Cloud API documentation') and provides a specific directive ('Call this first before searching'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from its sibling 'index_prisma_docs', which appears similar, leaving some ambiguity about when to use one versus the other.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states 'Call this first before searching,' providing clear guidance on when to use this tool in relation to search operations. It implies a prerequisite step for searching, though it doesn't specify alternatives or exclusions beyond this sequencing advice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/clarkemn/prisma-cloud-docs-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server