Skip to main content
Glama
edgarrmondragon

LimeSurvey MCP Server

set_participant_properties

Update participant properties in LimeSurvey surveys using token and survey ID to manage respondent data.

Instructions

Set LimeSurvey participant properties.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYes
sidYes
propertiesYes

Implementation Reference

  • main.py:596-608 (handler)
    The handler function for the 'set_participant_properties' tool, decorated with @mcp.tool() for registration. It uses type hints for input schema (token: str, sid: int, properties: dict[str, Any]) and returns bool. The logic delegates to the LimeSurvey client's set_participant_properties method via a context-managed client.
    @mcp.tool()
    def set_participant_properties(
        token: str, sid: int, properties: dict[str, Any]
    ) -> bool:
        """Set LimeSurvey participant properties.
    
        Args:
            token: The participant token.
            sid: The survey ID.
            properties: The properties to set.
        """
        with get_client() as client:
            return client.set_participant_properties(token, sid, properties)
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 this is a mutation tool ('Set'), but doesn't describe what happens on success/failure, whether properties are merged or replaced, permission requirements, or side effects. This leaves significant gaps for a tool that modifies data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and front-loaded with the purpose, but the parameter listing is redundant with the schema and adds little value. While not verbose, it could be more efficiently structured by focusing on contextual guidance rather than repeating parameter names.

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?

For a mutation tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is insufficient. It lacks details on behavior, parameter meanings, error handling, and relationships to sibling tools, leaving the agent with inadequate context for reliable use.

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 the three parameters but provides no semantic context beyond their names—no explanation of what a 'participant token' is, what format 'properties' should take, or what 'sid' represents. This adds minimal value beyond the bare schema.

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 the resource 'LimeSurvey participant properties', making the purpose understandable. It doesn't explicitly distinguish from sibling tools like 'set_group_properties' or 'set_survey_properties', but the resource specificity is adequate for basic clarity.

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 'add_participants' or 'update_response', nor does it mention prerequisites such as needing an active survey or valid token. Usage context is implied only by the tool name and parameters.

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