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BioContextAI Knowledgebase MCP

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bc_get_antibody_list

Search the Antibody Registry to find antibodies by gene symbol, protein name, or UniProt ID. Retrieve catalog numbers, vendors, clonality, applications, and metadata for research.

Instructions

Search Antibody Registry for antibodies. Returns catalog numbers, vendors, clonality, applications, and metadata.

Returns: dict: Search results containing list of antibodies with catalog numbers, vendors, clonality, applications, metadata or error message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchYesGene symbol, protein name, or UniProt ID (e.g., 'TRPC6')
pageNoPage number for pagination (default: 1)
sizeNoNumber of results per page (default: API default)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Core implementation of the `get_antibody_list` tool handler, which queries the Antibody Registry API for antibodies based on gene symbol, protein name, or UniProt ID. This becomes `bc_get_antibody_list` when core_mcp is imported under the 'bc' prefix in the main app.
    @core_mcp.tool()
    def get_antibody_list(
        search: Annotated[str, Field(description="Gene symbol, protein name, or UniProt ID (e.g., 'TRPC6')")],
        page: Annotated[int | None, Field(description="Page number for pagination (default: 1)")] = None,
        size: Annotated[int | None, Field(description="Number of results per page (default: API default)")] = None,
    ) -> dict:
        """Search Antibody Registry for antibodies. Returns catalog numbers, vendors, clonality, applications, and metadata.
    
        Returns:
            dict: Search results containing list of antibodies with catalog numbers, vendors, clonality, applications, metadata or error message.
        """
        search = search.strip()
        if not search:
            return {"error": "Search term cannot be empty."}
    
        url = "https://www.antibodyregistry.org/api/fts-antibodies"
    
        params = {"q": search}
        if page is not None:
            params["page"] = page
        if size is not None:
            params["size"] = size
    
        headers = {"accept": "application/json"}
    
        try:
            response = requests.get(url, params=params, headers=headers)
            response.raise_for_status()
            return response.json()
        except requests.exceptions.RequestException as e:
            return {"error": f"Failed to fetch antibody information from Antibody Registry: {e!s}"}
  • Registers the antibodyregistry tools (including `get_antibody_list`) into `core_mcp` by importing the module, triggering the @tool decorator execution.
    from .antibodyregistry import *
  • Imports `core_mcp` (containing `get_antibody_list`) into the main `mcp_app` under the slugified name 'bc', prefixing tools as `bc_get_antibody_list`.
    for mcp in [core_mcp, *(await get_openapi_mcps())]:
        await mcp_app.import_server(
            mcp,
            slugify(mcp.name),
        )
    logger.info("MCP server setup complete.")
  • Pydantic schema definitions for input parameters and return type of the tool.
    def get_antibody_list(
        search: Annotated[str, Field(description="Gene symbol, protein name, or UniProt ID (e.g., 'TRPC6')")],
        page: Annotated[int | None, Field(description="Page number for pagination (default: 1)")] = None,
        size: Annotated[int | None, Field(description="Number of results per page (default: API default)")] = None,
    ) -> dict:
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool returns search results or error messages, but doesn't describe important behavioral aspects like whether this is a read-only operation, rate limits, authentication requirements, or what happens with invalid searches. The description is minimal and lacks behavioral context beyond basic functionality.

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 reasonably concise but has structural issues. The first sentence is clear, but the 'Returns:' section is redundant since an output schema exists. The description could be more front-loaded with critical information and eliminate the redundant return value explanation.

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 has 3 parameters with full schema coverage and an output schema exists, the description is minimally adequate. However, for a search tool with no annotations, it should provide more context about search behavior, result format, and error conditions. The existence of an output schema means the description doesn't need to explain return values, but it should still cover behavioral aspects.

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?

With 100% schema description coverage, the baseline is 3. The description doesn't add any parameter information beyond what's already in the schema - it doesn't explain search semantics, pagination behavior, or default values. The schema already documents all three parameters with good descriptions, so the description adds no additional parameter context.

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 tool searches the Antibody Registry for antibodies and returns specific fields (catalog numbers, vendors, clonality, applications, metadata). It specifies the resource (Antibody Registry) and verb (search), but doesn't explicitly differentiate from sibling tools like 'bc_get_antibody_information' which might retrieve detailed information about a specific antibody rather than search.

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. There's no mention of when this search tool is appropriate compared to other antibody-related tools like 'bc_get_antibody_information' or other search tools in the sibling list. 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.

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