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rspace-os

RSpace MCP Server

Official
by rspace-os

status

Check RSpace server connectivity and system health to verify accessibility before performing operations.

Instructions

System health check - determines if RSpace server is accessible and running

Usage: Call this first to verify connectivity before other operations Returns: Status message from RSpace server

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • main.py:101-110 (handler)
    The handler function for the 'status' MCP tool. It performs a health check on the RSpace server by calling eln_cli.get_status() and returns the status message. Registered via the @mcp.tool decorator.
    @mcp.tool(tags={"rspace"})
    def status() -> str:
        """
        System health check - determines if RSpace server is accessible and running
        
        Usage: Call this first to verify connectivity before other operations
        Returns: Status message from RSpace server
        """
        resp = eln_cli.get_status()
        return resp['message']
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 behavior: it performs a health check, returns a status message, and has no parameters. However, it doesn't mention potential failure modes, authentication requirements, or rate limits, which would be helpful for a connectivity verification tool.

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 perfectly structured with three concise sentences: purpose statement, usage guideline, and return value explanation. Every sentence earns its place, and information is front-loaded with the core purpose stated first.

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 simplicity (0 parameters, no annotations, but has output schema), the description is complete. It explains what the tool does, when to use it, and what it returns. The output schema will handle return value details, so the description doesn't need to elaborate further.

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 baseline is 4. The description reinforces this by not mentioning any parameters, which is appropriate and adds no unnecessary information.

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 with specific verbs ('determines if RSpace server is accessible and running') and identifies the resource ('RSpace server'). It distinguishes itself from sibling tools by focusing on system health rather than data operations like document creation or sample management.

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 explicitly states when to use the tool ('Call this first to verify connectivity before other operations'), providing clear guidance on its role as a prerequisite for other operations. This directly addresses when-to-use context without needing to specify exclusions.

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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