MCP Duty Pharma
The MCP Duty Pharma server helps you locate pharmacies legally required to stay open during nights, weekends, and holidays.
Locate Nearby Duty Pharmacies: Find the ten closest pharmacies on duty today, sorted by distance to a specified address using the
get_nearby_duty_pharmaciestool.Safe Usage: Implements rate limiting and error handling to prevent excessive requests.
Integration: Easily installable in Claude Desktop or other environments.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Duty Pharmafind pharmacies open near me right now"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Duty Pharma
MCP Duty Pharma helps you locate pharmacies legally required to stay open during nights, weekends, and holidays. Whether it's an emergency or just a late-night need, this tool ensures you always know where to go.
📋 System Requirements
Python 3.10+
Related MCP server: Hong Kong Health Data MCP Server
📦 Dependencies
Install all required dependencies:
# Using uv
uv syncRequired Packages
fastmcp: Framework for building Model Context Protocol servers
geoPy: Python library for accessing and geocoding/reverse geocoding locations.
httpx: HTTP client for Python, which provides a simple and intuitive API for making HTTP requests.
All dependencies are specified in pyproject.toml.
📑 Table of Contents
🛠️ MCP Tools
This MCP server provides the following tools to Large Language Models (LLMs):
get_nearby_duty_pharmacies
Get ten closest pharmacies on duty today, sorted by distance to the given address.
📦 Installation
You can install this MCP server in either Claude Desktop or elsewhere. To use this server, add the following configuration to the settings file:
in json format
{
"MCP Duty Pharma": {
"command": "uv",
"args": ["tool", "run", "mcp_duty_pharma"]
}
}in yaml format
mcpServers:
- name: MCP Duty Pharma
command: uv
args:
- tool
- run
- mcp_duty_pharma🔒 Safety Features
Rate Limiting: Each geocoding call is rate-limited (e.g., 1-second delay) to avoid excessive requests that violate usage limits.
Error Handling: Catches geopy exceptions (timeouts, service errors) and returns safe [] results instead of crashing.
📚 Development Documentation
If you’d like to extend or modify this server:
Check duty-pharma.py for how each tool is implemented and how duty-pharma is integrated.
Look at geopy’s official docs for advanced usage like bounding boxes, language settings, or advanced data extraction.
Look at regional government APIs for more data sources.
Available Tools
1 toolget_nearby_duty_pharmaciesB
Get ten closest pharmacies on duty today, sorted by distance to the given address.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
TDQS
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. While it mentions the tool returns 'ten closest pharmacies' and sorts by distance, it fails to describe critical behaviors such as response format, error handling, data freshness, rate limits, or authentication requirements. For a location-based query tool with zero annotation coverage, this leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the core functionality: action, resource, quantity, constraints, and sorting. Every word earns its place with no redundancy or fluff, making it easy to parse and front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (location-based query with filtering), lack of annotations, and no output schema, the description is minimally complete. It covers the basic purpose and parameter intent but omits details on output structure, error cases, and operational constraints. It meets the bare minimum for understanding what the tool does but not how it behaves fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate. It adds meaning by explaining that the 'address' parameter is used to calculate distance and filter results, which goes beyond the schema's bare 'Address' title. However, it doesn't specify address format requirements, validation rules, or handling of ambiguous inputs, leaving some semantic gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get ten closest pharmacies on duty today, sorted by distance to the given address.' It specifies the verb ('Get'), resource ('pharmacies'), and key constraints ('ten closest', 'on duty today', 'sorted by distance'). However, with no sibling tools mentioned, it cannot demonstrate differentiation from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. It implies usage for finding nearby duty pharmacies but offers no information about prerequisites, limitations, or scenarios where other tools might be more appropriate. With no siblings listed, this is a missed opportunity for basic context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- First observed
get_nearby_duty_pharmacies
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.
A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The tool name follows a clear verb_noun pattern (get_nearby_duty_pharmacies).
One tool is too few for a server with a domain like pharmacy duty information, as it lacks essential operations such as filtering by time, getting pharmacy details, or updating duty status. This severely limits agent functionality.
The tool surface is severely incomplete for the domain; it only provides a list of nearby duty pharmacies without supporting operations like checking specific pharmacy hours, verifying duty status, or managing pharmacy data, leading to significant gaps in agent workflows.
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