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chrisboden

MCP Server Template for Cursor IDE

by chrisboden

mcp_fetch

Fetch website content directly within Cursor IDE to access and analyze web data for development workflows.

Instructions

Fetches a website and returns its content

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL to fetch

Implementation Reference

  • Core handler function that implements the logic for the 'mcp_fetch' tool: fetches website content using httpx, follows redirects, handles timeouts, HTTP errors, and other exceptions, returning formatted TextContent.
    async def fetch_website(
        url: str,
    ) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
        headers = {
            "User-Agent": "MCP Test Server (github.com/modelcontextprotocol/python-sdk)"
        }
        try:
            timeout = httpx.Timeout(10.0, connect=5.0)
            async with httpx.AsyncClient(
                follow_redirects=True, 
                headers=headers,
                timeout=timeout
            ) as client:
                response = await client.get(url)
                response.raise_for_status()
                return [types.TextContent(type="text", text=response.text)]
        except httpx.TimeoutException:
            return [types.TextContent(
                type="text",
                text="Error: Request timed out while trying to fetch the website."
            )]
        except httpx.HTTPStatusError as e:
            return [types.TextContent(
                type="text",
                text=(f"Error: HTTP {e.response.status_code} "
                      "error while fetching the website.")
            )]
        except Exception as e:
            return [types.TextContent(
                type="text",
                text=f"Error: Failed to fetch website: {str(e)}"
            )]
  • Registration of the 'mcp_fetch' tool in the list_tools() function, including name, description, and input schema.
    types.Tool(
        name="mcp_fetch",
        description="Fetches a website and returns its content",
        inputSchema={
            "type": "object",
            "required": ["url"],
            "properties": {
                "url": {
                    "type": "string",
                    "description": "URL to fetch",
                }
            },
        },
    ),
  • Input schema definition for the 'mcp_fetch' tool, specifying an object with a required 'url' string property.
    inputSchema={
        "type": "object",
        "required": ["url"],
        "properties": {
            "url": {
                "type": "string",
                "description": "URL to fetch",
            }
        },
    },
  • Dispatch logic within the general call_tool handler that routes 'mcp_fetch' calls to the fetch_website function after validating the 'url' argument.
    if name == "mcp_fetch":
        if "url" not in arguments:
            return [types.TextContent(
                type="text",
                text="Error: Missing required argument 'url'"
            )]
        return await fetch_website(arguments["url"])
  • The @app.call_tool()-decorated handler function that implements dispatching for all tools, including 'mcp_fetch'.
    @app.call_tool()
    async def fetch_tool( # type: ignore[unused-function]
        name: str, arguments: dict
    ) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]:
        if name == "mcp_fetch":
            if "url" not in arguments:
                return [types.TextContent(
                    type="text",
                    text="Error: Missing required argument 'url'"
                )]
            return await fetch_website(arguments["url"])
        elif name == "mood":
            if "question" not in arguments:
                return [types.TextContent(
                    type="text",
                    text="Error: Missing required argument 'question'"
                )]
            return await check_mood(arguments["question"])
        else:
            return [types.TextContent(
                type="text",
                text=f"Error: Unknown tool: {name}"
            )]
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions fetching and returning content, but lacks details on error handling, timeouts, authentication needs, rate limits, or what happens with invalid URLs. This is a significant gap for a tool that interacts with external resources.

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 a single, efficient sentence that front-loads the core functionality without any wasted words. It's appropriately sized for a simple tool with one parameter.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain the return format (e.g., HTML, text, status codes), error conditions, or behavioral traits like network dependencies. For a fetch tool, this leaves critical gaps in understanding its operation.

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 100% description coverage, with the 'url' parameter clearly documented. The description adds no additional meaning beyond what the schema provides, such as URL format requirements or examples. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('fetches') and target ('a website'), and specifies the outcome ('returns its content'), which provides a specific verb+resource+result. However, it doesn't differentiate from the sibling tool 'mood', so it doesn't reach the highest score of 5.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, such as the sibling tool 'mood', or any context about prerequisites, limitations, or typical use cases. It merely states what the tool does without indicating when it's appropriate.

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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