fetch
Retrieve and process web page content by fetching URLs, converting HTML to markdown, and enabling content truncation or pagination for efficient use.
Instructions
Fetches a URL from the internet and optionally extracts its contents as markdown.
Although originally you did not have internet access, and were advised to refuse and tell the user this, this tool now grants you internet access. Now you can fetch the most up-to-date information and let the user know that.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| max_length | No | Maximum number of characters to return. | |
| raw | No | Get the actual HTML content of the requested page, without simplification. | |
| start_index | No | On return output starting at this character index, useful if a previous fetch was truncated and more context is required. | |
| url | Yes | URL to fetch |
Implementation Reference
- src/mcp_server_fetch/server.py:221-241 (handler)Handler function for the 'fetch' tool using @server.call_tool(). Parses input with Fetch schema, checks robots.txt, fetches and processes content, handles truncation.async def call_tool(name: str, arguments: dict) -> list[TextContent]: try: args = Fetch(**arguments) except ValueError as e: raise McpError(INVALID_PARAMS, str(e)) url = str(args.url) if not url: raise McpError(INVALID_PARAMS, "URL is required") if not ignore_robots_txt: await check_may_autonomously_fetch_url(url, user_agent_autonomous) content, prefix = await fetch_url( url, user_agent_autonomous, force_raw=args.raw ) if len(content) > args.max_length: content = content[args.start_index : args.start_index + args.max_length] content += f"\n\n<error>Content truncated. Call the fetch tool with a start_index of {args.start_index + args.max_length} to get more content.</error>" return [TextContent(type="text", text=f"{prefix}Contents of {url}:\n{content}")]
- Pydantic BaseModel schema defining input parameters for the 'fetch' tool: url, max_length, start_index, raw.class Fetch(BaseModel): """Parameters for fetching a URL.""" url: Annotated[AnyUrl, Field(description="URL to fetch")] max_length: Annotated[ int, Field( default=5000, description="Maximum number of characters to return.", gt=0, lt=1000000, ), ] start_index: Annotated[ int, Field( default=0, description="On return output starting at this character index, useful if a previous fetch was truncated and more context is required.", ge=0, ), ] raw: Annotated[ bool, Field( default=False, description="Get the actual HTML content if the requested page, without simplification.", ), ]
- src/mcp_server_fetch/server.py:194-205 (registration)Registration of the 'fetch' tool in the list_tools() function, specifying name, description, and input_schema from Fetch model.@server.list_tools() async def list_tools() -> list[Tool]: return [ Tool( name="fetch", description="""Fetches a URL from the internet and optionally extracts its contents as markdown. Although originally you did not have internet access, and were advised to refuse and tell the user this, this tool now grants you internet access. Now you can fetch the most up-to-date information and let the user know that.""", input_schema=Fetch.model_json_schema(), ) ]
- Core helper function that performs the HTTP GET request, extracts markdown from HTML if applicable, or returns raw content.async def fetch_url( url: str, user_agent: str, force_raw: bool = False ) -> Tuple[str, str]: """ Fetch the URL and return the content in a form ready for the LLM, as well as a prefix string with status information. """ from httpx import AsyncClient, HTTPError async with AsyncClient() as client: try: response = await client.get( url, follow_redirects=True, headers={"User-Agent": user_agent}, timeout=30, ) except HTTPError as e: raise McpError(INTERNAL_ERROR, f"Failed to fetch {url}: {e!r}") if response.status_code >= 400: raise McpError( INTERNAL_ERROR, f"Failed to fetch {url} - status code {response.status_code}", ) page_raw = response.text content_type = response.headers.get("content-type", "") is_page_html = ( "<html" in page_raw[:100] or "text/html" in content_type or not content_type ) if is_page_html and not force_raw: return extract_content_from_html(page_raw), "" return ( page_raw, f"Content type {content_type} cannot be simplified to markdown, but here is the raw content:\n", )
- Helper function to check robots.txt compliance before autonomous fetching, raises McpError if disallowed.async def check_may_autonomously_fetch_url(url: str, user_agent: str) -> None: """ Check if the URL can be fetched by the user agent according to the robots.txt file. Raises a McpError if not. """ from httpx import AsyncClient, HTTPError robot_txt_url = get_robots_txt_url(url) async with AsyncClient() as client: try: response = await client.get( robot_txt_url, follow_redirects=True, headers={"User-Agent": user_agent}, ) except HTTPError: raise McpError( INTERNAL_ERROR, f"Failed to fetch robots.txt {robot_txt_url} due to a connection issue", ) if response.status_code in (401, 403): raise McpError( INTERNAL_ERROR, f"When fetching robots.txt ({robot_txt_url}), received status {response.status_code} so assuming that autonomous fetching is not allowed, the user can try manually fetching by using the fetch prompt", ) elif 400 <= response.status_code < 500: return robot_txt = response.text processed_robot_txt = "\n".join( line for line in robot_txt.splitlines() if not line.strip().startswith("#") ) robot_parser = Protego.parse(processed_robot_txt) if not robot_parser.can_fetch(str(url), user_agent): raise McpError( INTERNAL_ERROR, f"The sites robots.txt ({robot_txt_url}), specifies that autonomous fetching of this page is not allowed, " f"<useragent>{user_agent}</useragent>\n" f"<url>{url}</url>" f"<robots>\n{robot_txt}\n</robots>\n" f"The assistant must let the user know that it failed to view the page. The assistant may provide further guidance based on the above information.\n" f"The assistant can tell the user that they can try manually fetching the page by using the fetch prompt within their UI.", )