Skip to main content
Glama
edgarrmondragon

LimeSurvey MCP Server

by edgarrmondragon
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

add_quota

Add a quota to a LimeSurvey survey to control participant responses based on specific criteria.

Instructions

Add a quota to a LimeSurvey survey.

Args:
    sid: The survey ID.
    quota_data: The quota data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sidYes
quota_dataYes

Implementation Reference

  • main.py:634-644 (handler)
    The MCP tool handler for 'add_quota'. Decorated with @mcp.tool(), it creates a context-managed Citric Client instance and delegates the quota addition to the LimeSurvey server via client.add_quota(sid, quota_data). This is the core implementation of the tool logic.
    @mcp.tool()
def add_quota(sid: int, quota_data: dict[str, Any]) -> int:
    """Add a quota to a LimeSurvey survey.

    Args:
        sid: The survey ID.
        quota_data: The quota data.
    """
    with get_client() as client:
        return client.add_quota(sid, quota_data)
  • main.py:15-21 (helper)
    Helper function used by the add_quota handler (and others) to instantiate the Citric Client with credentials from environment variables.
    def get_client() -> Client:
    return Client(
        url=os.getenv("LIMESURVEY_URL"),
        username=os.getenv("LIMESURVEY_USERNAME"),
        password=os.getenv("LIMESURVEY_PASSWORD"),
    )
  • main.py:634-634 (registration)
    The @mcp.tool() decorator registers the add_quota function as an MCP tool.
    @mcp.tool()

Tool Definition Quality

C2.9/5.0
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 the tool adds a quota but doesn't explain what that entails—whether it's a creation operation, if it requires specific permissions, what happens on success/failure, or if there are rate limits. This leaves significant gaps in understanding the tool's behavior beyond the basic action.

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 a clear first sentence stating the purpose, followed by a brief parameter list. There's no wasted text, and it's front-loaded with the main action. However, the parameter descriptions are very minimal, which slightly reduces efficiency, but overall it's well-structured.

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 complexity (2 parameters with nested objects, no annotations, no output schema), the description is incomplete. It doesn't explain what a 'quota' is in LimeSurvey context, how the addition affects the survey, what the return value might be, or error conditions. For a mutation tool with undocumented parameters, this leaves too many unknowns for effective use.

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

Parameters3/5

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 parameters ('sid' and 'quota_data') and provides minimal context ('survey ID' and 'quota data'), but doesn't elaborate on formats, constraints, or examples (e.g., what 'quota_data' should contain). This adds some meaning beyond the bare schema but falls short of fully documenting the parameters, especially the complex 'quota_data' object.

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 action ('Add a quota') and the target resource ('to a LimeSurvey survey'), providing specific verb+resource pairing. However, it doesn't distinguish this tool from other quota-related tools like 'delete_quota' or 'set_quota_properties' among the sibling tools, which prevents a perfect score.

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?

No guidance is provided on when to use this tool versus alternatives like 'set_quota_properties' or 'delete_quota'. The description lacks context about prerequisites, such as whether the survey must be active or if quotas are limited, and doesn't mention any exclusions or specific scenarios for its application.

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