Skip to main content
Glama
godzeo
by godzeo

http_put

Send HTTP PUT requests with headers, cookies, and body, configure timeout, and log all request details. Ideal for API testing, security checks, and web automation.

Instructions

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNo
cookiesNo
headersNo
timeoutNo
urlYes

Implementation Reference

  • The primary handler function for the 'http_put' tool. It is registered via the @mcp.tool() decorator, which also defines the input schema through type hints and default values. The function performs an HTTP PUT request by delegating to the shared 'make_http_request_with_logging' helper.
    @mcp.tool()
    def http_put(
        url: str, 
        headers: Optional[Dict[str, str]] = None,
        cookies: Optional[Dict[str, str]] = None,
        body: Optional[str] = None,
        timeout: float = 30.0
    ) -> str:
        """HTTP PUT request with full support (headers, cookies, body, timeout) - All requests logged"""
        try:
            result = make_http_request_with_logging("PUT", 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 implements the actual HTTP PUT (and other methods) request logic using httpx.Client. It handles the request execution, response capture, and invokes logging. This is the exact implementation of the tool's core functionality.
    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 helper that logs the full request and response details 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
  • Creation of the FastMCP server instance where all tools including http_put are registered via decorators.
    mcp = FastMCP("HTTP Requests")
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It adds that 'All requests logged', which is useful context about side effects. However, it lacks critical details: whether this is idempotent (typical for PUT), authentication requirements, error handling, rate limits, or what the response contains. For a mutation tool with zero annotation coverage, this is insufficient.

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 zero waste. It's front-loaded with the core purpose and includes key features without redundancy. Every word earns its place, making it highly concise and well-structured.

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 complexity (HTTP mutation tool with 5 parameters), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It mentions logging but omits essential context: response format, error behavior, idempotency, authentication, and typical use cases. This leaves the agent under-informed 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, body, timeout) in parentheses, adding some meaning beyond the schema's property names. However, it doesn't explain parameter purposes (e.g., timeout in seconds, body format) or constraints, leaving significant gaps. The baseline is lowered due to poor schema coverage, but the description provides minimal compensation.

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 PUT request' with 'full support (headers, cookies, body, timeout)', which specifies the verb (PUT request) and resources (HTTP endpoints). It distinguishes from siblings by mentioning PUT specifically, though it doesn't explicitly contrast with other HTTP methods like POST or PATCH.

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_patch. It mentions 'full support' but doesn't explain typical PUT use cases (e.g., updating resources) or prerequisites, leaving the agent to infer usage from the HTTP method name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/godzeo/mcp-requests'

If you have feedback or need assistance with the MCP directory API, please join our Discord server