Configuring Timeout Settings for HTTP Requests in Python MCP Servers

You can configure HTTP request timeouts in Python MCP servers by modifying the timeout parameter in the requests.get() call, using module-level constants for centralized control, or leveraging environment variables for deployment flexibility.

The cr2007/mcp-wordle-python repository demonstrates how a FastMCP-based server handles external API calls using the Python requests library. Configuring timeout settings for HTTP requests in Python MCP servers is essential to prevent hanging processes and ensure reliable tool execution when calling external services like the Wordle API.

Current Timeout Implementation

In src/mcp_wordle/main.py, the get_wordle_data function makes an HTTP request with a hardcoded timeout of 300 seconds (5 minutes):

# src/mcp_wordle/main.py (lines 66-67)

return requests.get(url, timeout=300).json()

This inline approach provides a safeguard against indefinite hangs but lacks flexibility for different deployment environments. The server entry point at lines 70-71 initializes the FastMCP server:

if __name__ == "__main__":
    mcp.run()

Because MCP servers run as short-lived processes, the HTTP timeout serves as the primary defense against resource exhaustion when external APIs respond slowly.

Three Methods to Configure HTTP Timeouts

Depending on your operational requirements, you can implement timeout configuration using three distinct approaches.

Inline Argument Modification

The simplest method changes the timeout value directly in the requests.get() call. This approach works best for quick fixes or when the timeout requirement is truly static.

# src/mcp_wordle/main.py

# Reduced from 300 seconds to 30 seconds

return requests.get(url, timeout=30).json()

While straightforward, this method requires code changes for every adjustment and scatters configuration logic throughout your source files.

Module-Level Constants

Centralizing timeout values as constants improves maintainability. Define a module-level variable in src/mcp_wordle/main.py and reference it across all HTTP requests:

# src/mcp_wordle/main.py

DEFAULT_TIMEOUT = 30  # seconds

def get_wordle_data():
    # ...

    return requests.get(url, timeout=DEFAULT_TIMEOUT).json()

This approach consolidates configuration at the top of your file, making it easier to adjust timeouts during development without hunting through function implementations.

Environment Variable Configuration

For production deployments using Docker or uvx, environment variables provide the most flexibility. Modify src/mcp_wordle/main.py to read from os.getenv() with a sensible default:

# src/mcp_wordle/main.py

import os

DEFAULT_TIMEOUT = int(os.getenv("WORDLE_TIMEOUT", "30"))

def get_wordle_data():
    # ...

    return requests.get(url, timeout=DEFAULT_TIMEOUT).json()

This method allows operators to adjust timeouts without rebuilding the container or modifying source code, which is critical for infrastructure-as-code workflows.

Docker Deployment Configuration

When deploying via Docker (as documented in the repository's README), pass the timeout variable through the MCP server configuration:

{
  "mcpServers": {
    "Wordle MCP (Python)": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i", "--init",
        "-e", "WORDLE_TIMEOUT=45",
        "ghcr.io/cr2007/mcp-wordle-python:latest"
      ]
    }
  }
}

The pyproject.toml file confirms that requests is declared as a dependency (lines 7-10), ensuring that the timeout parameter is fully supported in the runtime environment.

Balancing Timeout Settings

Adjusting timeout values requires balancing two competing concerns:

• Responsiveness: Setting timeouts too short may cause legitimate API responses to fail on slow or flaky networks, resulting in false errors for MCP tool calls.
• Resource Usage: Excessively long timeouts tie up the MCP process, delaying subsequent requests and potentially exhausting container resources during high-load scenarios.

The current 300-second default accommodates slow Wordle API responses but may be excessive for responsive deployments. Reducing this to 30-45 seconds typically provides adequate buffer while preventing resource starvation.

Summary

• Primary configuration location: The timeout is set in src/mcp_wordle/main.py within the requests.get() call at lines 66-67.
• Inline modification: Change the hardcoded value for quick adjustments, though this offers the least flexibility.
• Constants approach: Use module-level variables to centralize timeout configuration for easier maintenance.
• Environment variables: Implement os.getenv() patterns to allow runtime configuration without code changes, ideal for Docker deployments.
• FastMCP compatibility: Timeout adjustments do not affect the tool registration or function signatures, preserving compatibility with existing MCP clients.

Frequently Asked Questions

How do I change the HTTP timeout without modifying source code?

Set the WORDLE_TIMEOUT environment variable when launching the container. The server can read this variable using os.getenv("WORDLE_TIMEOUT", "30") to override default values, allowing configuration through your MCP client settings or Docker orchestration tools.

What is the default timeout in the Wordle MCP server?

According to the source code in src/mcp_wordle/main.py, the default timeout is 300 seconds (5 minutes), specified directly in the requests.get(url, timeout=300) call. This value accommodates potentially slow responses from the external Wordle API.

Why does my MCP server hang when calling external APIs?

Without explicit timeout configuration, HTTP requests may wait indefinitely for server responses. Ensure your requests.get() calls include a timeout parameter, or implement the environment variable pattern described above to prevent the FastMCP process from hanging on unresponsive endpoints.

Does changing the timeout affect the MCP tool registration?

No. Modifying the HTTP timeout value does not change the function signature of get_wordle_data or the FastMCP tool registration. The timeout operates internally within the function and remains transparent to the MCP protocol layer.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}