Skip to main content
Glama
edgarrmondragon

LimeSurvey MCP Server

set_survey_properties

Configure survey settings in LimeSurvey by updating properties like title, dates, or access rules for a specific survey ID.

Instructions

Set LimeSurvey survey properties.

Args:
    sid: The survey ID.
    properties: The properties to set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sidYes
propertiesYes

Implementation Reference

  • main.py:425-434 (handler)
    The @mcp.tool()-decorated handler function implementing the set_survey_properties tool. It uses a LimeSurvey Client to set the specified properties for the given survey ID.
    @mcp.tool()
    def set_survey_properties(sid: int, properties: dict[str, Any]) -> bool:
        """Set LimeSurvey survey properties.
    
        Args:
            sid: The survey ID.
            properties: The properties to set.
        """
        with get_client() as client:
            return client.set_survey_properties(sid, properties)
  • main.py:425-425 (registration)
    The @mcp.tool() decorator registers the set_survey_properties function as an MCP tool.
    @mcp.tool()
  • main.py:15-20 (helper)
    Helper function to create and return a LimeSurvey Client instance used by the tool handler.
    def get_client() -> Client:
        return Client(
            url=os.getenv("LIMESURVEY_URL"),
            username=os.getenv("LIMESURVEY_USERNAME"),
            password=os.getenv("LIMESURVEY_PASSWORD"),
        )
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 states 'Set' implies a mutation operation but doesn't specify permissions required, whether changes are reversible, rate limits, or what happens to unspecified properties. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.

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 with three sentences: a purpose statement followed by parameter listings. It's front-loaded with the core functionality. However, the parameter section is overly terse and could benefit from more detail without sacrificing conciseness.

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

Completeness2/5

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

Given the tool's complexity (mutation with nested object parameter), lack of annotations, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't cover behavioral aspects, parameter details, or usage context, making it inadequate for safe and effective tool invocation by an AI agent.

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. It lists both parameters ('sid' and 'properties') but provides minimal semantics: 'sid' is described as 'The survey ID' (basic), and 'properties' as 'The properties to set' (vague). It doesn't explain what properties are available, their formats, or constraints, failing to compensate for the schema's lack of descriptions.

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 ('Set') and resource ('LimeSurvey survey properties'), making the purpose specific and understandable. It distinguishes this from other tools like 'set_group_properties' or 'set_question_properties' by specifying it's for survey-level properties. However, it doesn't explicitly differentiate from 'set_participant_properties' or 'set_quota_properties' beyond the resource name.

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. It doesn't mention prerequisites (e.g., needing an existing survey), exclusions, or compare it to sibling tools like 'add_survey' (for creation) or 'update_response' (for response data). The agent must infer usage from the tool name alone.

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/edgarrmondragon/limesurvey-mcp'

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