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godzeo
by godzeo

http_head

Perform HTTP HEAD requests with customizable headers, cookies, and timeout settings. Logs all requests for detailed tracking, enabling efficient web and API testing.

Instructions

HTTP HEAD request with full support (headers, cookies, timeout) - All requests logged

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cookiesNo
headersNo
timeoutNo
urlYes

Implementation Reference

  • The main handler function for the 'http_head' MCP tool. It uses the shared 'make_http_request_with_logging' helper to perform the HTTP HEAD request, handles parameters like url, headers, cookies, timeout, and returns JSON-formatted results including logging info.
    @mcp.tool()
    def http_head(
        url: str, 
        headers: Optional[Dict[str, str]] = None,
        cookies: Optional[Dict[str, str]] = None,
        timeout: float = 30.0
    ) -> str:
        """HTTP HEAD request with full support (headers, cookies, timeout) - All requests logged"""
        try:
            result = make_http_request_with_logging("HEAD", url, headers or {}, cookies or {}, "", timeout)
            return json.dumps(result, indent=2)
        except Exception as e:
            return f"Error: {str(e)}"
  • Shared helper function that performs the actual HTTP request using httpx, logs the full request/response details, and returns structured results. Used by all http_* tools including http_head.
    def make_http_request_with_logging(method: str, url: str, headers: dict, cookies: dict, body: str, timeout: float):
        """Universal HTTP request function with logging"""
        try:
            with httpx.Client(timeout=timeout) as client:
                response = client.request(
                    method=method.upper(),
                    url=url,
                    headers=headers,
                    cookies=cookies,
                    content=body.encode('utf-8') if body else None
                )
                
                # Log the request and response
                log_path = log_request_response(
                    method=method.upper(), 
                    url=url, 
                    headers=headers, 
                    cookies=cookies, 
                    body=body,
                    status_code=response.status_code,
                    response_headers=dict(response.headers),
                    response_content=response.text,
                    response_length=len(response.text)
                )
                
                return {
                    "method": method.upper(),
                    "url": url,
                    "status_code": response.status_code,
                    "response_headers": dict(response.headers),
                    "response_content": response.text,
                    "response_length": len(response.text),
                    "request_headers": headers,
                    "request_cookies": cookies,
                    "request_body": body,
                    "logged_to": log_path
                }
        except Exception as e:
            # Log the error
            log_request_response(
                method=method.upper(), url=url, headers=headers, cookies=cookies, body=body,
                status_code=0, response_headers={}, response_content="", response_length=0,
                error=str(e)
            )
            raise e
  • Helper function that logs detailed request and response information to a timestamped file in ~/mcp_requests_logs/.
    def log_request_response(method: str, url: str, headers: dict, cookies: dict, body: str, 
                            status_code: int, response_headers: dict, response_content: str, 
                            response_length: int, error: str = None):
        """Log complete request and response details"""
        log_data = {
            "timestamp": datetime.datetime.now().isoformat(),
            "request": {
                "method": method,
                "url": url,
                "headers": headers,
                "cookies": cookies,
                "body": body,
                "body_length": len(body) if body else 0
            },
            "response": {
                "status_code": status_code if not error else "ERROR",
                "headers": response_headers if not error else {},
                "content_length": response_length if not error else 0,
                "content_preview": response_content[:500] + "..." if response_content and len(response_content) > 500 else response_content
            },
            "error": error
        }
        
        logger.info(f"HTTP_REQUEST: {json.dumps(log_data, indent=2, ensure_ascii=False)}")
        return log_path
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions logging and full support for features, but lacks details on error handling, response format, rate limits, authentication needs, or what 'full support' entails. This is inadequate for a network tool with potential side effects.

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 with no wasted words. It front-loads the core action (HTTP HEAD request) and lists key features directly.

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 no annotations, no output schema, and 0% schema coverage, the description is incomplete. It omits critical details like response behavior, error cases, and practical usage context, making it insufficient for safe and effective tool invocation.

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?

Schema description coverage is 0%, so the description must compensate. It lists parameters (headers, cookies, timeout) and implies a URL, but doesn't explain their purposes, formats, or constraints (e.g., timeout units, cookie structure). This adds minimal value beyond the schema's property names.

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 tool performs an 'HTTP HEAD request' with specific features (headers, cookies, timeout) and mentions logging. It distinguishes from siblings by specifying the HTTP method (HEAD vs GET/POST/etc.), but doesn't explicitly differentiate the purpose beyond the method name.

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?

No guidance is provided on when to use HEAD vs other HTTP methods (like GET for retrieving body content) or alternatives. The description mentions features but not typical use cases (e.g., checking resource existence, headers without body).

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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