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mcp-clinical-doc-agent

mcp-clinical-doc-agent

by Aditya-Khadye
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_documents

Discover available clinical trial protocol documents by retrieving their IDs, titles, indications, and phases to select documents for entity extraction or summarization.

Instructions

List all clinical trial protocol documents available in the data directory.

Returns one entry per protocol with id, title, path, indication, and phase.
Use this tool first to discover what documents are available, then pass an
``id`` from the result to ``extract_entities`` or ``summarize_protocol``.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_documents"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden. It discloses the output structure (id, title, path, indication, phase) and that it lists all documents. It does not mention read-only nature or potential side effects, but for a list tool this is generally implicit. Slight gap but acceptable.

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 three sentences, each serving a clear purpose: define the action, detail the output, and provide usage context. No unnecessary words.

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

Completeness4/5

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

Given no parameters and an output schema, the description sufficiently explains what the tool does and what it returns. It could mention edge cases or error conditions, but for a straightforward list tool, it is largely complete.

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 input schema has 0 parameters, so the baseline is 4. The description does not need to add parameter information, and it correctly omits any.

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 tool lists all clinical trial protocol documents, specifies the return fields (id, title, path, indication, phase), and explicitly distinguishes from siblings by suggesting subsequent use of extract_entities or summarize_protocol.

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

Usage Guidelines5/5

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

The description directly advises to use this tool first to discover available documents, then pass the id from its result to the sibling tools extract_entities or summarize_protocol, providing clear workflow guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

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