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Rootly-AI-Labs

Rootly MCP server

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createEnvironment

Generate a new environment by specifying name, description, color, and associated notifications. Handles responses for success, unauthorized access, or invalid requests.

Instructions

Creates a new environment from provided data

Responses:

  • 201 (Success): environment created

    • Content-Type: application/vnd.api+json

    • Example:

{
  "key": "value"
}
  • 401: responds with unauthorized for invalid token

    • Content-Type: application/vnd.api+json

    • Example:

{
  "key": "value"
}
  • 422: invalid request

    • Content-Type: application/vnd.api+json

    • Example:

{
  "key": "value"
}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Registration of all dynamic OpenAPI tools, including "createEnvironment" generated from POST /environments endpoint via FastMCP.from_openapi
    # By default, all routes become tools which is what we want
    mcp = FastMCP.from_openapi(
        openapi_spec=filtered_spec,
        client=http_client.client,
        name=name,
        timeout=30.0,
        tags={"rootly", "incident-management"},
    )
  • DEFAULT_ALLOWED_PATHS includes "/environments" enabling the createEnvironment tool (POST /environments)
        "/environments",
        "/environments/{environment_id}",
        # Users
        "/users",
        "/users/{user_id}",
        "/users/me",
        # Status pages
        "/status_pages",
        "/status_pages/{status_page_id}",
        # On-call schedules and shifts
        "/schedules",
        "/schedules/{schedule_id}",
        "/schedules/{schedule_id}/shifts",
        "/shifts",
        "/schedule_rotations/{schedule_rotation_id}",
        "/schedule_rotations/{schedule_rotation_id}/schedule_rotation_users",
        "/schedule_rotations/{schedule_rotation_id}/schedule_rotation_active_days",
        # On-call overrides
        "/schedules/{schedule_id}/override_shifts",
        "/override_shifts/{override_shift_id}",
        # On-call shadows and roles
        "/schedules/{schedule_id}/on_call_shadows",
        "/on_call_shadows/{on_call_shadow_id}",
        "/on_call_roles",
        "/on_call_roles/{on_call_role_id}",
    ]
  • AuthenticatedHTTPXClient.request: the generic handler executing all proxied API calls, including createEnvironment (proxies POST /v1/environments)
    async def request(self, method: str, url: str, **kwargs):
        """Override request to transform parameters."""
        # Transform query parameters
        if 'params' in kwargs:
            kwargs['params'] = self._transform_params(kwargs['params'])
    
        # Call the underlying client's request method and let it handle everything
        return await self.client.request(method, url, **kwargs)
  • sanitize_parameters_in_spec processes the OpenAPI spec, defining input schemas for all tools including createEnvironment
    parameter_mapping = sanitize_parameters_in_spec(filtered_spec)
    logger.info(f"Sanitized parameter names for MCP compatibility (mapped {len(parameter_mapping)} parameters)")
  • AuthenticatedHTTPXClient: supporting class that handles authentication, parameter transformation, and HTTP requests for all generated tools including createEnvironment
    class AuthenticatedHTTPXClient:
        """An HTTPX client wrapper that handles Rootly API authentication and parameter transformation."""
    
        def __init__(self, base_url: str = "https://api.rootly.com", hosted: bool = False, parameter_mapping: Optional[Dict[str, str]] = None):
            self._base_url = base_url
            self.hosted = hosted
            self._api_token = None
            self.parameter_mapping = parameter_mapping or {}
    
            if not self.hosted:
                self._api_token = self._get_api_token()
    
            # Create the HTTPX client  
            headers = {
                "Content-Type": "application/vnd.api+json", 
                "Accept": "application/vnd.api+json"
                # Let httpx handle Accept-Encoding automatically with all supported formats
            }
            if self._api_token:
                headers["Authorization"] = f"Bearer {self._api_token}"
    
            self.client = httpx.AsyncClient(
                base_url=base_url,
                headers=headers,
                timeout=30.0,
                follow_redirects=True,
                # Ensure proper handling of compressed responses
                limits=httpx.Limits(max_keepalive_connections=5, max_connections=10)
            )
    
        def _get_api_token(self) -> Optional[str]:
            """Get the API token from environment variables."""
            api_token = os.getenv("ROOTLY_API_TOKEN")
            if not api_token:
                logger.warning("ROOTLY_API_TOKEN environment variable is not set")
                return None
            return api_token
    
        def _transform_params(self, params: Optional[Dict[str, Any]]) -> Optional[Dict[str, Any]]:
            """Transform sanitized parameter names back to original names."""
            if not params or not self.parameter_mapping:
                return params
    
            transformed = {}
            for key, value in params.items():
                # Use the original name if we have a mapping, otherwise keep the sanitized name
                original_key = self.parameter_mapping.get(key, key)
                transformed[original_key] = value
                if original_key != key:
                    logger.debug(f"Transformed parameter: '{key}' -> '{original_key}'")
            return transformed
    
        async def request(self, method: str, url: str, **kwargs):
            """Override request to transform parameters."""
            # Transform query parameters
            if 'params' in kwargs:
                kwargs['params'] = self._transform_params(kwargs['params'])
    
            # Call the underlying client's request method and let it handle everything
            return await self.client.request(method, url, **kwargs)
    
        async def get(self, url: str, **kwargs):
            """Proxy to request with GET method."""
            return await self.request('GET', url, **kwargs)
    
        async def post(self, url: str, **kwargs):
            """Proxy to request with POST method."""
            return await self.request('POST', url, **kwargs)
    
        async def put(self, url: str, **kwargs):
            """Proxy to request with PUT method."""
            return await self.request('PUT', url, **kwargs)
    
        async def patch(self, url: str, **kwargs):
            """Proxy to request with PATCH method."""
            return await self.request('PATCH', url, **kwargs)
    
        async def delete(self, url: str, **kwargs):
            """Proxy to request with DELETE method."""
            return await self.request('DELETE', url, **kwargs)
    
        async def __aenter__(self):
            return self
    
        async def __aexit__(self, exc_type, exc_val, exc_tb):
            pass
    
        def __getattr__(self, name):
            # Delegate all other attributes to the underlying client, except for request methods
            if name in ['request', 'get', 'post', 'put', 'patch', 'delete']:
                # Use our overridden methods instead
                return getattr(self, name)
            return getattr(self.client, name)
        
        @property 
        def base_url(self):
            return self._base_url
            
        @property
        def headers(self):
            return self.client.headers
Behavior3/5

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 HTTP response codes (201, 401, 422) and content types, which adds useful context about success, authentication errors, and invalid requests. However, it lacks details on permissions, side effects, rate limits, or what 'environment' means in this context, leaving gaps for a creation tool.

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

Conciseness3/5

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

The description is front-loaded with the core purpose but includes verbose HTTP response details that may not all be necessary for an AI agent. The response examples are generic and repetitive, adding bulk without unique value. It could be more streamlined by focusing on essential behavioral insights rather than full API documentation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (1 parameter with nested objects), no annotations, and an output schema present, the description is moderately complete. It covers basic behavioral aspects like response codes but misses key details: parameter semantics, differentiation from siblings, and context about what an 'environment' entails. The output schema reduces the need to explain return values, but gaps remain in usage and input guidance.

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

Parameters2/5

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 for undocumented parameters. It only states 'from provided data' without explaining the input structure or meaning. The input schema has 1 parameter with nested properties (e.g., name, color, slack_channels), but the description adds no semantic details beyond what's inferred from the schema, failing to address the coverage 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's purpose: 'Creates a new environment from provided data.' This specifies the verb ('creates') and resource ('environment'), making it easy to understand what the tool does. However, it doesn't differentiate from sibling tools like 'createService' or 'createTeam', which follow similar patterns for different resources.

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. It doesn't mention prerequisites (e.g., authentication), differentiate from similar creation tools in the sibling list, or specify use cases. The only implied context is from the name 'createEnvironment', but no explicit usage instructions are given.

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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