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meilisearch

Meilisearch MCP Server

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by meilisearch

get-health-status

Retrieve comprehensive health status details for Meilisearch, enabling proactive monitoring and troubleshooting through the Meilisearch MCP Server.

Instructions

Get comprehensive health status of Meilisearch

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The MCP tool handler in the call_tool function that executes get-health-status by calling the monitoring manager's get_health_status method and formatting the result as text content.
    elif name == "get-health-status":
        status = self.meili_client.monitoring.get_health_status()
        self.logger.info("Health status checked", status=status.__dict__)
        return [
            types.TextContent(
                type="text",
                text=f"Health status: {json.dumps(status.__dict__, default=json_serializer)}",
            )
        ]
  • Registration of the get-health-status tool in the list_tools handler, including its name, description, and input schema.
    types.Tool(
        name="get-health-status",
        description="Get comprehensive health status of Meilisearch",
        inputSchema={
            "type": "object",
            "properties": {},
            "additionalProperties": False,
        },
    ),
  • Helper function in MonitoringManager that implements the core logic for retrieving comprehensive health status from Meilisearch, aggregating stats and index information.
    def get_health_status(self) -> HealthStatus:
        """Get comprehensive health status"""
        try:
            # Get various stats to build health picture
            stats = self.client.get_all_stats()
            indexes = self.client.get_indexes()
    
            indexes_info = []
            for index in indexes:
                index_stats = self.client.index(index.uid).get_stats()
                indexes_info.append(
                    {
                        "uid": index.uid,
                        "documents_count": index_stats["numberOfDocuments"],
                        "is_indexing": index_stats["isIndexing"],
                    }
                )
    
            return HealthStatus(
                is_healthy=True,
                database_size=stats["databaseSize"],
                last_update=datetime.fromisoformat(
                    stats["lastUpdate"].replace("Z", "+00:00")
                ),
                indexes_count=len(indexes),
                indexes_info=indexes_info,
            )
        except Exception as e:
            raise Exception(f"Failed to get health status: {str(e)}")
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe response format, error conditions, rate limits, or authentication requirements. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a simple tool and front-loads the essential information about what the tool does.

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 simplicity (0 parameters, no output schema), the description adequately covers the basic purpose. However, without annotations or output schema, it should ideally provide more context about what 'comprehensive health status' includes or the response format to help the agent understand what to expect.

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?

The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't waste space discussing nonexistent parameters, earning a baseline score of 4 for zero-parameter tools.

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 verb ('Get') and resource ('comprehensive health status of Meilisearch'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'health-check' or 'get-system-info', but the specificity of 'comprehensive health status' provides some implicit distinction.

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 like 'health-check' or 'get-system-info'. There's no mention of prerequisites, timing, or comparative context with sibling tools, leaving the agent to infer usage scenarios.

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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