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qwert666

Foundry MCP Server

by qwert666
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

list_functions

Discover available functions in the Foundry MCP Server to interact with datasets and ontology objects using natural language queries.

Instructions

List all available functions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/mcp_server_foundry/server.py:120-128 (handler)
    The handler function for the 'list_functions' tool. It retrieves and returns the list of available query types (functions) from the Foundry ontology using the provided context.
    @mcp.tool()
def list_functions(ctx: Context) -> Iterator[str]:
    """ List all available functions"""

    foundry_client: FoundryClient = ctx.request_context.lifespan_context.foundry_client
    ontology_id: str = ctx.request_context.lifespan_context.ontology_id

    return [ontologyType for ontologyType in foundry_client.ontologies.Ontology.QueryType.list(ontology_id)]

Tool Definition Quality

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states it lists functions but doesn't disclose behavioral traits like whether it's read-only, paginated, rate-limited, or what format the output is in. This is a significant gap for a tool with zero annotation coverage.

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 a single, efficient sentence with no wasted words. It's front-loaded and appropriately sized for a simple tool, making it easy to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain return values, behavioral constraints, or how it fits with siblings, leaving gaps in understanding for the agent despite the tool's simplicity.

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, and schema description coverage is 100%, so there's no need for parameter details in the description. The baseline for 0 parameters is 4, as the description doesn't need to compensate for any missing param info.

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 ('List') and resource ('all available functions'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_ontology_types' or 'query_ontology_type', which might also list things, so it's not fully distinguished.

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 context, prerequisites, or compare to siblings like 'execute_function' or 'query_dataset', leaving the agent with no usage direction.

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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