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BioContextAI Knowledgebase MCP

BioContextAI Knowledgebase MCP

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by biocontext-ai
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Python
Hybrid

bc_get_drug_by_application_number

Retrieve detailed information about an FDA-approved drug by its application number, including application details, products, and sponsor.

Instructions

Get detailed information about an FDA-approved drug by application number. Format: NDA/ANDA/BLA followed by 6 digits.

Returns: dict: FDA drug results with application details, products, sponsor information or error message.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "application_number": "<application_number>"
    },
    "name": "bc_get_drug_by_application_number"
  }
}

Input Schema

NameRequiredDescriptionDefault
application_numberYesFDA application number (e.g., 'NDA021436', 'ANDA123456', 'BLA761234')

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.0
    • removedInput schema / properties / application_number / title
      Removed value: -"Application Number"
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden. It discloses that the tool returns a dict with application details, products, sponsor info, or an error message. It does not explicitly state it's read-only, but the 'Get' verb implies a safe read operation. The return type and possible error are mentioned.

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?

Two sentences: first states purpose and input format, second describes return. No redundant words. Front-loaded with key information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (single parameter, simple lookup) and presence of an output schema (so return structure can be inferred), the description is complete. It covers input format, what the tool does, and the type of output.

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 schema already describes the parameter with examples. The description adds the formatting rule 'NDA/ANDA/BLA followed by 6 digits', which adds clarity beyond the schema examples. Schema coverage is 100%, so the baseline is 3; the added format specifier raises it to 4.

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 verb 'Get' and resource 'detailed information about an FDA-approved drug', and specifies the input format (application number with prefix and 6 digits). It distinguishes from sibling search tools (e.g., bc_search_drugs_fda) by indicating this is a direct lookup by application number.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when you have an application number in the correct format. It does not explicitly state when not to use or provide alternatives, but the sibling tools include search functions, making the context clear.

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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