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godzeo
by godzeo

http_get

Send HTTP GET requests with configurable headers, cookies, body, and timeout. Logs all request details for security testing, API testing, or web automation.

Instructions

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNo
cookiesNo
headersNo
timeoutNo
urlYes

Implementation Reference

  • The http_get tool handler, including registration via @mcp.tool(), input schema via type annotations and defaults, and execution logic that invokes the shared HTTP helper function.
    @mcp.tool()
    def http_get(
        url: str, 
        headers: Optional[Dict[str, str]] = None,
        cookies: Optional[Dict[str, str]] = None,
        body: Optional[str] = None,
        timeout: float = 30.0
    ) -> str:
        """HTTP GET request with full support (headers, cookies, body, timeout) - All requests logged"""
        try:
            result = make_http_request_with_logging("GET", url, headers or {}, cookies or {}, body or "", timeout)
            return json.dumps(result, indent=2)
        except Exception as e:
            return f"Error: {str(e)}"
  • Core helper function that performs the actual HTTP request using httpx, handles logging, error cases, and formats the response dictionary. Used by http_get and all other HTTP method tools.
    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
  • Supporting utility that logs detailed request and response information to a file in ~/mcp_requests_logs/ with timestamps.
    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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions logging ('All requests logged'), which adds some context, but fails to address critical traits like error handling, response format, authentication needs, or rate limits. For a network tool with zero annotation coverage, this is inadequate.

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

Conciseness4/5

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

The description is concise (one sentence) and front-loaded with the core purpose. However, the phrase 'with full support' is vague and could be trimmed for clarity, slightly reducing efficiency.

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 5 parameters with 0% schema coverage, no annotations, no output schema, and sibling tools, the description is incomplete. It lacks details on parameter usage, behavioral expectations (e.g., response handling), and differentiation from siblings, making it insufficient for effective tool selection.

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

Parameters1/5

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

Schema description coverage is 0%, meaning parameters are undocumented in the schema. The description lists parameters (headers, cookies, body, timeout) but provides no semantic details—e.g., what format headers/cookies should be in, what body content is allowed for GET, or timeout units. It doesn't compensate for the schema gap.

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 GET request' with specific capabilities (headers, cookies, body, timeout), which is a specific verb+resource combination. However, it doesn't explicitly distinguish this from its sibling tools (http_delete, http_post, etc.) beyond the GET method, missing differentiation that would earn a 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 like http_post or http_raw_request. It mentions 'full support' but doesn't specify scenarios where GET is appropriate (e.g., retrieving data vs. sending data), leaving the agent without usage context.

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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