Skip to main content
Glama

spix_sms_list

Retrieve and filter SMS messages from a real phone number, enabling AI agents to manage inbound and outbound communications with pagination support.

Instructions

List SMS messages

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
playbook_idNoFilter by playbook
directionNoFilter by direction
limitNoNumber of results
cursorNoPagination cursor

Implementation Reference

  • The generic tool handler that dispatches MCP tool calls (including 'spix_sms_list') to the backend API.
    async def create_tool_handler(
        session: McpSessionContext,
        tool_name: str,
        arguments: dict,
    ) -> list:
        """Execute an MCP tool call by dispatching to the backend API.
    
        This function:
        1. Resolves the tool name to a command schema
        2. Validates session scope (playbook access, channel access)
        3. Builds the API request
        4. Dispatches to the backend
        5. Returns the response as MCP TextContent
    
        Args:
            session: The MCP session context for scope validation.
            tool_name: The MCP tool name (e.g., "spix_playbook_create").
            arguments: The tool arguments from the MCP client.
    
        Returns:
            List containing a single TextContent with the JSON response.
        """
        # Import here to avoid circular imports and handle missing mcp package
        try:
            from mcp.types import TextContent
        except ImportError:
            # Fallback for when mcp is not installed
            class TextContent:  # type: ignore[no-redef]
                def __init__(self, type: str, text: str) -> None:
                    self.type = type
                    self.text = text
    
        # Resolve tool name to schema
        schema = get_schema_by_tool_name(tool_name)
        if not schema:
            return [
                TextContent(
                    type="text",
                    text=orjson.dumps(
                        {"ok": False, "error": {"code": "unknown_tool", "message": f"Unknown tool: {tool_name}"}}
                    ).decode(),
                )
            ]
    
        # Validate tool access (not disabled)
        try:
            session.validate_tool_access(schema.path)
        except Exception as e:
            from spix_mcp.session import McpScopeError
    
            if isinstance(e, McpScopeError):
                return [TextContent(type="text", text=orjson.dumps({"ok": False, "error": e.to_dict()}).decode())]
            raise
    
        # Validate channel access if applicable
        channel = infer_channel_from_tool(schema.path)
        if channel:
            try:
                session.validate_channel_access(channel)
            except Exception as e:
                from spix_mcp.session import McpScopeError
    
                if isinstance(e, McpScopeError):
                    return [TextContent(type="text", text=orjson.dumps({"ok": False, "error": e.to_dict()}).decode())]
                raise
    
        # Handle playbook_id: validate and apply default
        playbook_id = arguments.get("playbook_id")
        try:
            effective_playbook = session.validate_playbook_access(playbook_id)
            if effective_playbook and not playbook_id:
                # Apply default playbook
                arguments["playbook_id"] = effective_playbook
        except Exception as e:
            from spix_mcp.session import McpScopeError
    
            if isinstance(e, McpScopeError):
                return [TextContent(type="text", text=orjson.dumps({"ok": False, "error": e.to_dict()}).decode())]
            raise
    
        # Build endpoint URL with path parameters
        endpoint, remaining_args = build_endpoint_url(schema, arguments)
    
        # Dispatch to backend API
        client = session.client
        method = schema.http_method.lower()
    
        if method == "get":
            response = await asyncio.to_thread(client.get, endpoint, params=remaining_args if remaining_args else None)
        elif method == "post":
            response = await asyncio.to_thread(client.post, endpoint, json=remaining_args if remaining_args else None)
        elif method == "patch":
            response = await asyncio.to_thread(client.patch, endpoint, json=remaining_args if remaining_args else None)
        elif method == "delete":
            response = await asyncio.to_thread(client.delete, endpoint, params=remaining_args if remaining_args else None)
        else:
            response = await asyncio.to_thread(client.get, endpoint)
    
        # Build response envelope
        envelope: dict = {"ok": response.ok, "meta": response.meta}
        if response.ok:
            envelope["data"] = response.data
            if response.pagination:
                envelope["pagination"] = response.pagination
            if response.warnings:
                envelope["warnings"] = response.warnings
        else:
            envelope["error"] = response.error
    
        return [TextContent(type="text", text=orjson.dumps(envelope).decode())]
  • The schema definition for the 'sms.list' command, which is mapped to the 'spix_sms_list' MCP tool name at runtime.
        path="sms.list",
        cli_usage="spix sms list [--playbook <id>]",
        http_method="GET",
        api_endpoint="/sms",
        mcp_expose="tool",
        mcp_profile="safe",
        description="List SMS messages",
        params=[
            CommandParam("playbook_id", "string", description="Filter by playbook"),
            CommandParam("direction", "enum", choices=["inbound", "outbound"], description="Filter by direction"),
            CommandParam("limit", "integer", default=50, description="Number of results"),
            CommandParam("cursor", "string", description="Pagination cursor"),
        ],
    ),
Behavior2/5

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 but offers minimal information. It states the action ('List') but doesn't describe key behaviors: whether this is a read-only operation, if it requires specific permissions, how pagination works (implied by the 'cursor' parameter but not explained), rate limits, or what the output looks like (e.g., list format, error handling). This leaves significant gaps for safe and effective tool invocation.

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 extremely concise—just three words—and front-loaded with the core action. There is no wasted language or unnecessary elaboration, making it easy to parse quickly. However, this conciseness comes at the cost of completeness, as noted in other dimensions.

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 tool's complexity (4 parameters, no output schema, and no annotations), the description is insufficiently complete. It lacks details on behavioral traits (e.g., read-only nature, pagination behavior), usage context compared to siblings, and output expectations. While the schema covers parameters well, the description fails to compensate for missing annotations and output schema, leaving the agent with incomplete guidance for proper tool selection and 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?

The input schema has 100% description coverage, so parameters like 'playbook_id', 'direction', 'limit', and 'cursor' are well-documented in the schema itself. The description adds no additional semantic context beyond implying filtering (via 'List SMS messages'), which doesn't enhance understanding of individual parameters. This meets the baseline of 3, as the schema adequately covers parameter details without extra help from the description.

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 'List SMS messages' clearly states the verb ('List') and resource ('SMS messages'), making the basic purpose understandable. However, it doesn't differentiate this tool from sibling tools like spix_sms_thread (which likely handles threaded SMS conversations) or spix_call_list (which lists calls rather than SMS), leaving room for ambiguity about when to choose this specific listing tool.

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 sibling tools like spix_sms_thread for threaded views or spix_contact_history for message history by contact, nor does it specify prerequisites (e.g., authentication) or typical use cases (e.g., monitoring inbound/outbound SMS). Without this context, an agent might struggle to select the appropriate tool.

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

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/Spix-HQ/spix-mcp'

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