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ryu1maniwa

OpenTelemetry Documentation MCP Server

by ryu1maniwa

read_documentation

Fetch OpenTelemetry documentation pages and convert them to markdown format for easy reading and reference.

Instructions

Fetch and convert a OpenTelemetry documentation page to markdown format.

Usage

This tool retrieves the content of a OpenTelemetry documentation page and converts it to markdown format. For long documents, you can make multiple calls with different start_index values to retrieve the entire content in chunks.

URL Requirements

  • Must be from the opentelemetry.io domain

  • Must be a documentation page

Example URLs

  • https://opentelemetry.io/docs/concepts/observability-primer/

  • https://opentelemetry.io/docs/instrumentation/

  • https://opentelemetry.io/docs/collector/

Output Format

The output is formatted as markdown text with:

  • Preserved headings and structure

  • Code blocks for examples

  • Lists and tables converted to markdown format

Handling Long Documents

If the response indicates the document was truncated, you have several options:

  1. Continue Reading: Make another call with start_index set to the end of the previous response

  2. Stop Early: For very long documents (>30,000 characters), if you've already found the specific information needed, you can stop reading

Args: ctx: MCP context for logging and error handling url: URL of the OpenTelemetry documentation page to read max_length: Maximum number of characters to return start_index: On return output starting at this character index

Returns: Markdown content of the OpenTelemetry documentation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL of the OpenTelemetry documentation page to read
max_lengthNoMaximum number of characters to return.
start_indexNoOn return output starting at this character index, useful if a previous fetch was truncated and more content is required.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The primary handler function for the 'read_documentation' tool. Decorated with @mcp.tool() for registration. Validates URL domain, fetches page with httpx, determines if HTML, extracts content to markdown, formats with pagination support (start_index, max_length), and returns truncated markdown with continuation prompt if needed.
    async def read_documentation(
        ctx: Context,
        url: Union[AnyUrl, str] = Field(description='URL of the OpenTelemetry documentation page to read'),
        max_length: int = Field(
            default=5000,
            description='Maximum number of characters to return.',
            gt=0,
            lt=1000000,
        ),
        start_index: int = Field(
            default=0,
            description='On return output starting at this character index, useful if a previous fetch was truncated and more content is required.',
            ge=0,
        ),
    ) -> str:
        """Fetch and convert a OpenTelemetry documentation page to markdown format.
    
        ## Usage
    
        This tool retrieves the content of a OpenTelemetry documentation page and converts it to markdown format.
        For long documents, you can make multiple calls with different start_index values to retrieve
        the entire content in chunks.
    
        ## URL Requirements
    
        - Must be from the opentelemetry.io domain
        - Must be a documentation page
    
        ## Example URLs
    
        - https://opentelemetry.io/docs/concepts/observability-primer/
        - https://opentelemetry.io/docs/instrumentation/
        - https://opentelemetry.io/docs/collector/
    
        ## Output Format
    
        The output is formatted as markdown text with:
        - Preserved headings and structure
        - Code blocks for examples
        - Lists and tables converted to markdown format
    
        ## Handling Long Documents
    
        If the response indicates the document was truncated, you have several options:
    
        1. **Continue Reading**: Make another call with start_index set to the end of the previous response
        2. **Stop Early**: For very long documents (>30,000 characters), if you've already found the specific information needed, you can stop reading
    
        Args:
            ctx: MCP context for logging and error handling
            url: URL of the OpenTelemetry documentation page to read
            max_length: Maximum number of characters to return
            start_index: On return output starting at this character index
    
        Returns:
            Markdown content of the OpenTelemetry documentation
        """
        # Validate that URL is from opentelemetry.io
        url_str = str(url)
        if not re.match(r'^https?://opentelemetry\.io/', url_str):
            await ctx.error(f'Invalid URL: {url_str}. URL must be from the opentelemetry.io domain')
            raise ValueError('URL must be from the opentelemetry.io domain')
    
        logger.debug(f'Fetching documentation from {url_str}')
    
        async with httpx.AsyncClient() as client:
            try:
                response = await client.get(
                    url_str,
                    follow_redirects=True,
                    headers={'User-Agent': DEFAULT_USER_AGENT},
                    timeout=30,
                )
            except httpx.HTTPError as e:
                error_msg = f'Failed to fetch {url_str}: {str(e)}'
                logger.error(error_msg)
                await ctx.error(error_msg)
                return error_msg
    
            if response.status_code >= 400:
                error_msg = f'Failed to fetch {url_str} - status code {response.status_code}'
                logger.error(error_msg)
                await ctx.error(error_msg)
                return error_msg
    
            page_raw = response.text
            content_type = response.headers.get('content-type', '')
    
        if is_html_content(page_raw, content_type):
            content = extract_content_from_html(page_raw)
        else:
            content = page_raw
    
        result = format_documentation_result(url_str, content, start_index, max_length)
    
        # Log if content was truncated
        if len(content) > start_index + max_length:
            logger.debug(
                f'Content truncated at {start_index + max_length} of {len(content)} characters'
            )
    
        return result
  • Helper function called by the handler to slice the content based on start_index and max_length, add header with URL, and append truncation notice prompting for next pagination call.
    def format_documentation_result(url: str, content: str, start_index: int, max_length: int) -> str:
        """Format documentation result with pagination information.
    
        Args:
            url: Documentation URL
            content: Content to format
            start_index: Start index for pagination
            max_length: Maximum content length
    
        Returns:
            Formatted documentation result
        """
        original_length = len(content)
    
        if start_index >= original_length:
            return f'OpenTelemetry Documentation from {url}:\n\n<e>No more content available.</e>'
    
        # Calculate the end index, ensuring we don't go beyond the content length
        end_index = min(start_index + max_length, original_length)
        truncated_content = content[start_index:end_index]
    
        if not truncated_content:
            return f'OpenTelemetry Documentation from {url}:\n\n<e>No more content available.</e>'
    
        actual_content_length = len(truncated_content)
        remaining_content = original_length - (start_index + actual_content_length)
    
        result = f'OpenTelemetry Documentation from {url}:\n\n{truncated_content}'
    
        # Only add the prompt to continue fetching if there is still remaining content
        if remaining_content > 0:
            next_start = start_index + actual_content_length
            result += f'\n\n<e>Content truncated. Call the read_documentation tool with start_index={next_start} to get more content.</e>'
    
        return result
  • Helper function extracts the main documentation content from OpenTelemetry HTML pages using targeted selectors for opentelemetry.io structure, cleans unwanted elements, and converts to clean markdown format.
    def extract_content_from_html(html: str) -> str:
        """Extract and convert HTML content to Markdown format.
    
        Args:
            html: Raw HTML content to process
    
        Returns:
            Simplified markdown version of the content
        """
        if not html:
            return '<e>Empty HTML content</e>'
    
        try:
            # Parse HTML with BeautifulSoup
            soup = BeautifulSoup(html, 'html.parser')
    
            # Try to find the main content area
            main_content = None
    
            # Common content container selectors for OpenTelemetry documentation
            content_selectors = [
                '.td-content',  # opentelemetry.io uses this selector for main content
                'main',
                'article',
                '#content',
                '.content',
                '#body-content',
                "div[role='main']",
                '.td-main',
            ]
    
            # Try to find the main content using common selectors
            for selector in content_selectors:
                content = soup.select_one(selector)
                if content:
                    main_content = content
                    break
    
            # If no main content found, use the body
            if not main_content:
                main_content = soup.body if soup.body else soup
    
            # Remove navigation elements that might be in the main content
            nav_selectors = [
                'noscript',
                '.prevNext',
                '.docsite-footer',
                '.feedback',
                '.td-sidebar',
                '.td-sidebar-nav',
                '.td-page-meta',
                '.td-search',
            ]
    
            for selector in nav_selectors:
                for element in main_content.select(selector):
                    element.decompose()
    
            # Define tags to strip - these are elements we don't want in the output
            tags_to_strip = [
                'script',
                'style',
                'noscript',
                'meta',
                'link',
                'footer',
                'nav',
                'aside',
                'header',
                '.td-sidebar',
                '.td-sidebar-nav',
                '.td-page-meta',
                '.td-search',
                # Common unnecessary elements
                'js-show-more-buttons',
                'js-show-more-text',
                'feedback-container',
                'feedback-section',
                'doc-feedback-container',
                'doc-feedback-section',
                'warning-container',
                'warning-section',
                'cookie-banner',
                'cookie-notice',
                'copyright-section',
                'legal-section',
                'terms-section',
            ]
    
            # Use markdownify on the cleaned HTML content
            content = markdownify.markdownify(
                str(main_content),
                heading_style='ATX',
                autolinks=True,
                default_title=True,
                escape_asterisks=True,
                escape_underscores=True,
                newline_style='SPACES',
                strip=tags_to_strip,
            )
    
            if not content:
                return '<e>Page failed to be simplified from HTML</e>'
    
            return content
        except Exception as e:
            return f'<e>Error converting HTML to Markdown: {str(e)}</e>'
  • Helper function determines whether the fetched page content is HTML based on content and headers, used to decide extraction path.
    def is_html_content(page_raw: str, content_type: str) -> bool:
        """Determine if content is HTML.
    
        Args:
            page_raw: Raw page content
            content_type: Content-Type header
    
        Returns:
            True if content is HTML, False otherwise
        """
        return '<html' in page_raw[:100] or 'text/html' in content_type or not content_type
  • The @mcp.tool() decorator registers the read_documentation function with the FastMCP server instance.
    async def read_documentation(
Behavior4/5

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

With no annotations provided, the description carries full burden and does an excellent job disclosing behavioral traits. It explains the conversion to markdown format, handling of long documents through chunking, URL domain restrictions, output format details, and strategies for dealing with truncated responses. The only minor gap is it doesn't mention rate limits or authentication requirements.

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 well-structured with clear sections (Usage, URL Requirements, Example URLs, Output Format, Handling Long Documents) and every sentence adds value. It's appropriately sized for a tool with this complexity and is front-loaded with the core purpose.

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

Completeness5/5

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

Given the tool's complexity (document fetching, conversion, chunking), no annotations, and the existence of an output schema, the description is remarkably complete. It covers purpose, usage guidelines, behavioral details, parameter context, output format, and handling edge cases like long documents. The output schema handles return values, so the description appropriately focuses on other aspects.

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?

With 100% schema description coverage, the baseline is 3. The description adds some value by explaining the purpose of start_index for chunking long documents and providing example URLs, but doesn't significantly enhance parameter understanding beyond what the schema already provides about url, max_length, and start_index.

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

Purpose5/5

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

The description clearly states the tool's purpose with specific verbs ('fetch and convert') and resource ('OpenTelemetry documentation page'), distinguishing it from the sibling 'search_documentation' tool by focusing on retrieving and converting specific pages rather than searching across documentation.

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 provides explicit usage guidelines, including when to use it (for OpenTelemetry documentation pages), when not to use it (must be from opentelemetry.io domain), and alternatives (making multiple calls with different start_index values for long documents). It also distinguishes from the sibling tool by specifying this is for reading specific pages.

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

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