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brukhabtu

Datadog MCP Server

by brukhabtu

GetSecurityMonitoringSignal

Retrieve detailed information about a specific security monitoring signal using its unique ID. This tool helps in analyzing and resolving security incidents by providing signal-specific data.

Instructions

Get a signal's details.

Path Parameters:

  • signal_id (Required): The ID of the signal.

Responses:

  • 200 (Success): OK

    • Content-Type: application/json

    • Response Properties:

    • Example:

{
  "data": "unknown_type"
}
  • 404: Not Found

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}
  • 429: Too many requests

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
signal_idYesThe ID of the signal.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo

Implementation Reference

  • The route pattern for security monitoring endpoints, including GetSecurityMonitoringSignal, is whitelisted here as a safe read-only GET tool. This registers the tool via FastMCP OpenAPI route mapping.
    safe_endpoints = [
        # Metrics and time-series data
        r"^/api/v2/metrics.*",  # Query metrics data
        r"^/api/v2/query/.*",  # Time-series queries
        # Dashboards and visualizations
        r"^/api/v2/dashboards.*",  # Dashboard configurations
        r"^/api/v2/notebooks.*",  # Notebook data
        # Monitoring and alerts
        r"^/api/v2/monitors.*",  # Monitor configurations
        r"^/api/v2/downtime.*",  # Scheduled downtimes
        r"^/api/v2/synthetics.*",  # Synthetic tests
        # Logs and events
        r"^/api/v2/logs/events/search$",  # Search logs
        r"^/api/v2/logs/events$",  # List log events
        r"^/api/v2/logs/config.*",  # Log pipeline configs
        # APM and traces
        r"^/api/v2/apm/.*",  # APM data
        r"^/api/v2/traces/.*",  # Trace data
        r"^/api/v2/spans/.*",  # Span data
        # Infrastructure
        r"^/api/v2/hosts.*",  # Host information
        r"^/api/v2/tags.*",  # Tag management (read)
        r"^/api/v2/usage.*",  # Usage statistics
        # Service management
        r"^/api/v2/services.*",  # Service catalog
        r"^/api/v2/slos.*",  # Service level objectives
        r"^/api/v2/incidents.*",  # Incident management
        # Security and compliance
        r"^/api/v2/security_monitoring.*",  # Security signals
        r"^/api/v2/cloud_workload_security.*",  # CWS data
        # Teams and organization (read-only)
        r"^/api/v2/users.*",  # User information
        r"^/api/v2/roles.*",  # Role information
        r"^/api/v2/teams.*",  # Team structure
        # API metadata
        r"^/api/v2/api_keys$",  # List API keys (no create/delete)
        r"^/api/v2/application_keys$",  # List app keys (no create/delete)
    ]
  • Creates RouteMap entries that explicitly mark matching security monitoring endpoints (including GetSecurityMonitoringSignal) as MCPType.TOOL, registering them as available tools.
    filters.extend(
        RouteMap(
            pattern=pattern,
            methods=["GET"],
            mcp_type=MCPType.TOOL,
        )
        for pattern in safe_endpoints
    )
  • Initializes the FastMCP server with the OpenAPI spec and security route_maps, which exposes the GetSecurityMonitoringSignal tool (derived from Datadog API operationId) as an MCP tool.
    self.mcp_server = FastMCP.from_openapi(
        openapi_spec=openapi_spec,
        client=auth_client,
        route_maps=route_maps,
    )
  • Monkey patches FastMCP OpenAPI parser to handle parameter locations correctly, necessary for security monitoring tools (and others) to function properly.
    def patch_fastmcp_parameter_parsing() -> None:
        """Patch FastMCP to handle enum parameter locations correctly.
        
        This fixes an incompatibility where FastMCP expects parameter locations
        as strings (e.g., "path", "query") but receives enum objects from the
        OpenAPI spec parser (e.g., <ParameterLocation.PATH: 'path'>).
        """
        try:
            import fastmcp.utilities.openapi as openapi_utils
            
            # Store original function
            original_convert = getattr(openapi_utils.OpenAPIParser, '_convert_to_parameter_location', None)
            
            def patched_convert_to_parameter_location(self, param_in):
                """Patched parameter location converter that handles enum values."""
                # Convert enum to string if needed
                if hasattr(param_in, 'value'):
                    param_in = param_in.value
                elif hasattr(param_in, 'name'):
                    param_in = param_in.name.lower()
                
                # Call original function with string value
                if original_convert:
                    return original_convert(self, param_in)
                else:
                    # Fallback implementation
                    if param_in in ["path", "query", "header", "cookie"]:
                        return param_in
                    return "query"
            
            # Apply the patch
            if hasattr(openapi_utils, 'OpenAPIParser'):
                openapi_utils.OpenAPIParser._convert_to_parameter_location = patched_convert_to_parameter_location
                
        except ImportError:
            # If we can't import the modules, the patch won't work but we'll continue
            pass
    
    
    # Apply patches when module is imported
    patch_fastmcp_parameter_parsing()
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. While it mentions HTTP response codes (200, 404, 429) and error formats, it doesn't describe authentication requirements, rate limits, side effects, or what 'details' actually includes. The example response shows 'data': 'unknown_type' which is unhelpful for understanding the actual return structure.

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

Conciseness2/5

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

The description is poorly structured with excessive HTTP response documentation that belongs in an output schema rather than a description. The core purpose ('Get a signal's details') is buried under technical response details. While not verbose, it's inefficiently organized with information that doesn't help an AI agent understand when and how to use the tool.

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 tool with no annotations, 100% schema coverage, and an output schema exists, the description is incomplete. It focuses on HTTP response codes rather than explaining what 'details' means, how signals are identified, or the tool's role in the security monitoring context. The presence of an output schema means the description shouldn't document return values, but it still needs to provide better contextual guidance.

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 100% with the single parameter 'signal_id' fully documented in both schema and description. The description adds no additional semantic context beyond what's in the schema (both say 'The ID of the signal'), meeting the baseline for high schema coverage but not providing extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Get a signal's details' which clearly indicates a retrieval operation on a security monitoring signal. However, it doesn't distinguish this tool from sibling tools like 'ListSecurityMonitoringSignals' or 'GetSecurityMonitoringRule', leaving ambiguity about when to use this specific get operation versus other related tools.

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 about when to use this tool versus alternatives. The description doesn't mention prerequisites, when this tool is appropriate versus listing signals, or any contextual constraints. It simply states what the tool does 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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