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xack

Acknowledge processed entries in a Redis stream consumer group by providing the stream key, group name, and entry IDs. Returns confirmation or error.

Instructions

Acknowledge entries that were processed by a consumer group.

Args: key (str): The stream key. group_name (str): The consumer group name. entry_ids (List[str]): Entry IDs to acknowledge.

Returns: str: Confirmation message or an error message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes
group_nameYes
entry_idsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The xack tool handler function. Decorated with @mcp.tool(), it acknowledges processed entries in a Redis stream consumer group. Takes key, group_name, and entry_ids parameters, validates entry_ids is non-empty, calls Redis XACK, and returns a confirmation or error message.
    @mcp.tool()
    async def xack(key: str, group_name: str, entry_ids: List[str]) -> str:
        """Acknowledge entries that were processed by a consumer group.
    
        Args:
            key (str): The stream key.
            group_name (str): The consumer group name.
            entry_ids (List[str]): Entry IDs to acknowledge.
    
        Returns:
            str: Confirmation message or an error message.
        """
        if not entry_ids:
            return "At least one entry ID is required to acknowledge stream entries"
    
        try:
            r = RedisConnectionManager.get_connection()
            acknowledged = r.xack(key, group_name, *entry_ids)
            return (
                f"Successfully acknowledged {acknowledged} entr"
                f"{'y' if acknowledged == 1 else 'ies'} in group '{group_name}' on stream '{key}'"
            )
        except RedisError as e:
            return (
                f"Error acknowledging entries for consumer group '{group_name}' on stream "
                f"'{key}': {str(e)}"
            )
  • Registration of xack as an MCP tool via the @mcp.tool() decorator in src/tools/stream.py. The module is auto-discovered and loaded by load_tools() in src/common/server.py.
    @mcp.tool()
    async def xack(key: str, group_name: str, entry_ids: List[str]) -> str:
  • Type annotations define the input schema: key (str), group_name (str), entry_ids (List[str]). The docstring serves as the description for the tool.
    async def xack(key: str, group_name: str, entry_ids: List[str]) -> str:
        """Acknowledge entries that were processed by a consumer group.
    
        Args:
            key (str): The stream key.
            group_name (str): The consumer group name.
            entry_ids (List[str]): Entry IDs to acknowledge.
    
        Returns:
            str: Confirmation message or an error message.
        """
Behavior2/5

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

With no annotations, the description should fully disclose behavior. It states the action but does not explain side effects (e.g., whether entries are removed from history), required permissions, or error conditions beyond a generic error message. The return type is mentioned but not detailed.

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

Conciseness4/5

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

The description is structured as a docstring with clear sections (Args, Returns). It is concise, using minimal words to convey purpose. However, it could be slightly more compact by removing redundant mentions of argument types that are already in the schema.

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 moderate complexity (acknowledging stream entries) and the availability of an output schema (return type), the description covers the basic what and how. However, it lacks usage context, prerequisites (e.g., consumer group must exist), and behavioral details that would make it self-sufficient for an agent.

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

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, meaning property descriptions are missing. The description's 'Args:' section merely repeats the parameter names and types without adding meaning (e.g., what each parameter represents, constraints, or format). This adds no value over the schema.

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

Purpose5/5

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

The description clearly states the tool's purpose: acknowledging entries processed by a consumer group, which is a specific verb+resource combination. It is distinct from sibling tools like xdel (delete) or xreadgroup (read), so the purpose is unambiguous.

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 such as xdel or xreadgroup. Missing context like prerequisites (e.g., need to be a consumer group member) or when not to use it.

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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