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sanchorelaxo

OpenSimulator MCP Server

by sanchorelaxo

set

Execute management commands to configure and control OpenSimulator virtual world servers, including setting parameters, changing regions, restarting services, and saving data.

Instructions

Run a mutating/management command (set/change/restart/save/etc.).

Examples:

  • set log level debug

  • change region MyRegion

  • region restart notice "Restarting" 60

  • save oar region.oar

  • terrain load myterrain.r32

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commandYes
argsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'set' tool. Decorated with @mcp.tool() for registration. Takes a base command and optional args, builds the full command, and sends it to the OpenSimulator console via the global console client.
    @mcp.tool()
    async def set(command: str, args: str = "") -> str:
        """
        Run a mutating/management command (set/change/restart/save/etc.).
    
        Examples:
        - set log level debug
        - change region MyRegion
        - region restart notice \"Restarting\" 60
        - save oar region.oar
        - terrain load myterrain.r32
        """
        return await console.send_command(_build_command(command, args))
  • Helper function used by 'set' (and 'get') tools to construct the full console command from base command and args.
    def _build_command(base: str, args: str = "") -> str:
        base = base.strip()
        args = args.strip()
        return f"{base} {args}".strip()
  • Core helper method in OpenSimConsole class that sends a command to the OpenSimulator REST console, manages session, and retrieves the response. Called by the 'set' tool.
    async def send_command(self, command: str) -> str:
        if not self.session_id:
            await self.start_session()
    
        async with await self._get_client() as client:
            response = await client.post(
                f"{self.base_url}/SessionCommand/",
                data={"ID": self.session_id, "COMMAND": command},
            )
            if response.status_code != 200:
                raise Exception(
                    f"Command failed: {response.status_code} - {response.text}"
                )
    
            # Wait for command to be processed before reading response
            await asyncio.sleep(0.3)
    
            read_response = await client.post(
                f"{self.base_url}/ReadResponses/{self.session_id}/"
            )
            return read_response.text
  • The @mcp.tool() decorator registers the 'set' function as an MCP tool.
    @mcp.tool()
Behavior2/5

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 mentions 'mutating/management commands' and examples like 'restart' and 'save', implying destructive or state-changing operations, but fails to detail critical aspects such as required permissions, side effects, error handling, or rate limits, which are essential for safe tool invocation.

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 appropriately sized and front-loaded, starting with a clear purpose statement followed by relevant examples. Each example serves to illustrate usage without redundancy, making it efficient, though the lack of explicit guidelines slightly reduces its overall effectiveness.

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 complexity (mutating operations with 2 parameters, 0% schema coverage, and no annotations) but with an output schema present, the description is moderately complete. It covers the tool's purpose and provides usage examples, but lacks details on behavioral traits and parameter semantics, which are crucial for a mutation tool without annotations.

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

Parameters2/5

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 for undocumented parameters. It lists example commands that imply 'command' and 'args' parameters (e.g., 'set log level debug' uses both), but doesn't explain their semantics, valid values, or formatting rules beyond the examples, leaving significant gaps in parameter understanding.

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?

The description states the tool runs 'mutating/management commands' with examples like 'set/change/restart/save/etc.', which clarifies it performs various administrative actions. However, it doesn't explicitly distinguish this from sibling tools like 'get' (likely read-only) or 'run' (possibly execution-focused), leaving the differentiation implied rather than explicit.

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 'get' or 'run'. It lists example commands but doesn't specify contexts, prerequisites, or exclusions, such as whether it's for system-level changes or user-specific settings, leaving the agent to infer usage from examples alone.

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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