Skip to main content
Glama
thenvoi

Thenvoi MCP Server

Official
by thenvoi

mark_agent_message_processed

Mark agent messages as successfully processed to update delivery status and timestamps in the Thenvoi MCP Server system.

Instructions

Mark a message as successfully processed by the agent.

Completes the current processing attempt with a system-managed timestamp.
Call this when the agent finishes processing a message successfully.

This endpoint automatically:
- Sets the current attempt's completed_at timestamp (system-managed)
- Sets the current attempt status to "success"
- Sets the agent's processed_at timestamp (system-managed)
- Updates the agent's delivery status to "processed"

Note: Requires an active processing attempt. If no processing attempt exists,
returns a 422 error. Call mark_agent_message_processing first.

Args:
    chat_id: The unique identifier of the chat room (required).
    message_id: The ID of the message to mark as processed (required).

Returns:
    Success message confirming the message is marked as processed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chat_idYes
message_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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 effectively describes the tool's actions (setting timestamps, updating statuses) and error conditions (422 if no processing attempt), though it lacks details on permissions, rate limits, or idempotency. No contradiction with annotations exists.

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 well-structured and front-loaded with the core purpose, followed by detailed behavioral notes and parameter explanations. Every sentence adds value without redundancy, making it efficient and easy to parse.

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

Completeness5/5

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

Given the tool's complexity (state-changing operation with prerequisites) and no annotations, the description is complete: it covers purpose, usage guidelines, behavioral effects, error handling, parameters, and notes the existence of an output schema (returns success message). No significant gaps remain for agent understanding.

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

Parameters4/5

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. It adds meaningful context for both parameters by explaining 'chat_id' as 'unique identifier of the chat room' and 'message_id' as 'ID of the message to mark as processed', which clarifies their roles beyond the schema's basic titles.

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 specific action ('Mark a message as successfully processed') and resource ('message'), distinguishing it from siblings like 'mark_agent_message_failed' and 'mark_agent_message_processing' by focusing on successful completion. It explicitly defines the verb and target, avoiding tautology.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('Call this when the agent finishes processing a message successfully'), when not to use it ('Requires an active processing attempt'), and names the alternative prerequisite ('Call mark_agent_message_processing first'). This clearly differentiates it from sibling tools.

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/thenvoi/thenvoi-mcp'

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