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hlydecker

UCSC Genome Browser MCP Server

by hlydecker

list_ucsc_genomes

Retrieve available genome assemblies from the UCSC Genome Browser database to identify species and versions for genomic analysis.

Instructions

List all UCSC Genome Browser database genomes available on the database host.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler logic for the 'list_ucsc_genomes' tool: constructs the UCSC API URL '/list/ucscGenomes' with no parameters and fetches the JSON response using make_api_request.
    elif name == "list_ucsc_genomes":
        url = build_api_url("/list/ucscGenomes", {})
        result = await make_api_request(url)
  • Registration of the 'list_ucsc_genomes' tool in the list_tools() function, including its name, description, and empty input schema (no parameters required).
    Tool(
        name="list_ucsc_genomes",
        description="List all UCSC Genome Browser database genomes available on the database host.",
        inputSchema={
            "type": "object",
            "properties": {}
        }
    ),
  • Input schema for 'list_ucsc_genomes' tool: an empty object, indicating no input parameters are required.
    inputSchema={
        "type": "object",
        "properties": {}
    }
  • Helper function build_api_url used by the handler to construct the UCSC API endpoint URL with parameters separated by semicolons.
    def build_api_url(endpoint: str, params: dict[str, Any]) -> str:
        """Build the complete API URL with parameters."""
        # Filter out None values
        filtered_params = {k: v for k, v in params.items() if v is not None}
        
        # Convert parameters to URL format (using semicolons as per UCSC API spec)
        if filtered_params:
            param_str = ";".join(f"{k}={v}" for k, v in filtered_params.items())
            return f"{BASE_URL}{endpoint}?{param_str}"
        return f"{BASE_URL}{endpoint}"
  • Helper function make_api_request used by the handler to perform asynchronous HTTP GET request to the API URL and parse JSON response.
    async def make_api_request(url: str) -> dict[str, Any]:
        """Make an HTTP request to the UCSC API and return JSON response."""
        async with httpx.AsyncClient(timeout=30.0) as client:
            response = await client.get(url)
            response.raise_for_status()
            return response.json()
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes a read-only list operation but lacks details on potential limitations (e.g., rate limits, authentication needs, or what 'available on the database host' entails). The description is minimal and does not compensate for the absence of annotations.

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, clear sentence with no wasted words. It is front-loaded with the core action and resource, making it easy for an agent to parse quickly. Every part of the sentence contributes essential information.

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 simplicity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It covers the basic purpose but lacks details on behavioral aspects like response format or constraints, which could be helpful for a tool interacting with a database host.

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 no parameter documentation is needed. The description appropriately does not discuss parameters, earning a baseline score of 4 for not introducing unnecessary information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('List all') and resource ('UCSC Genome Browser database genomes available on the database host'), distinguishing it from siblings like 'list_genark_genomes' or 'list_hub_genomes' by specifying the exact database source. It uses precise terminology that helps the agent understand the scope.

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 'list_genark_genomes' or 'search_genome', nor does it mention any prerequisites or exclusions. It merely states what the tool does without contextual usage information.

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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