Skip to main content
Glama

memory_events_clear

Clear consumed events from memory to manage system resources and maintain organized event tracking in the Memora server.

Instructions

Mark events as consumed.

Args: event_ids: List of event IDs to mark as consumed

Returns: Dictionary with count of cleared events

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
event_idsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • Tool registration and implementation for memory_events_clear which calls _clear_events.
    @mcp.tool()
    async def memory_events_clear(event_ids: List[int]) -> Dict[str, Any]:
        """Mark events as consumed.
    
        Args:
            event_ids: List of event IDs to mark as consumed
    
        Returns:
            Dictionary with count of cleared events
        """
        cleared = _clear_events(event_ids)
        return {"cleared": cleared}
  • Helper function wrapping clear_events which executes the database operation.
    @_with_connection(writes=True)
    def _clear_events(conn, event_ids: List[int]):
        return clear_events(conn, event_ids)
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses the return value ('Dictionary with count of cleared events') which is helpful, but fails to explain what 'consumed' means (archived? deleted? flagged?), whether the operation is reversible, or error conditions (e.g., invalid IDs).

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?

Uses a structured Args/Returns format that is easy to parse. The first sentence immediately states the purpose. While the Returns section may be redundant if a formal output schema exists (per context signals), the content is efficient with no unnecessary prose.

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?

Sufficient for a single-parameter tool with no annotations, covering the basic operation and parameter meaning. However, given the existence of memory_events_poll as a sibling, the description is incomplete without explaining the event lifecycle workflow relationship.

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 0%, leaving the description to provide all semantic meaning. It explains that event_ids are used 'to mark as consumed,' adding purpose context beyond the schema's bare 'Event Ids' title. However, it omits constraints (max batch size) and source guidance (obtain IDs from memory_events_poll).

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?

States the core action ('Mark events as consumed') with a specific verb and resource, but uses jargon ('consumed') without defining the state change. Fails to distinguish from sibling memory_events_poll or clarify that this likely acknowledges events retrieved via polling.

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?

Provides no guidance on when to use this tool versus alternatives, nor does it mention the prerequisite workflow (typically calling memory_events_poll first to obtain the event_ids). No 'when-not-to-use' or prerequisites are documented.

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/agentic-box/memora'

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