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by godzeo

http_patch

Send HTTP PATCH requests with headers, cookies, body, and timeout settings. Logs all request details for API testing, security checks, and web automation tasks.

Instructions

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNo
cookiesNo
headersNo
timeoutNo
urlYes

Implementation Reference

  • The handler function for the 'http_patch' tool, decorated with @mcp.tool() for registration. Defines input schema via parameters and executes the PATCH request via helper.
    @mcp.tool()
    def http_patch(
        url: str, 
        headers: Optional[Dict[str, str]] = None,
        cookies: Optional[Dict[str, str]] = None,
        body: Optional[str] = None,
        timeout: float = 30.0
    ) -> str:
        """HTTP PATCH request with full support (headers, cookies, body, timeout) - All requests logged"""
        try:
            result = make_http_request_with_logging("PATCH", 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 implementing the HTTP request logic using httpx.Client, handling all HTTP methods including PATCH, and comprehensive logging of requests/responses.
    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 for detailed logging of HTTP requests and responses to file.
    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 full burden. It mentions logging behavior ('All requests logged') which is valuable, but fails to disclose critical behavioral traits like authentication requirements, error handling, rate limits, or what the response format looks like. For a network operation tool with zero annotation coverage, this leaves significant gaps.

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 efficiently structured in a single sentence that communicates the core functionality and key features. It's appropriately sized for the tool's complexity, though it could be slightly more front-loaded by starting with the primary purpose before listing capabilities.

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?

For a network operation tool with 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, authentication needs, or practical usage scenarios. The logging mention is helpful but doesn't compensate for the overall lack of context needed to use this tool effectively.

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 0% schema description coverage, the description doesn't add any parameter-specific information beyond what's implied by the tool name. It mentions 'headers, cookies, body, timeout' in a list but doesn't explain their purpose, format, or constraints. The baseline is 3 since the schema provides complete parameter definitions despite lacking descriptions.

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 PATCH request' with specific capabilities (headers, cookies, body, timeout) and mentions logging. It distinguishes itself from siblings by specifying the HTTP method (PATCH), but doesn't explicitly differentiate from other HTTP method tools 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?

The description provides no guidance on when to use this tool versus alternatives like http_post or http_put. It mentions 'full support' but doesn't explain when PATCH is appropriate compared to other HTTP methods, leaving the agent to infer usage from the method name alone.

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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