INDIAN MEDICINES (MCP SERVER)

Name: INDIAN MEDICINES (MCP SERVER)
Author: nowitsidb

@nowitsidb

INDIAN MEDICINES (MCP SERVER) について

A comprehensive API server for medicine information lookup, alternative suggestions, and composition analysis. This server provides multiple endpoints for searching, filtering, and analyzing medicine data with advanced features like fuzzy matching and price comparison.

#medicine #api #healthcare

基本情報

カテゴリ

その他

ランタイム

python

トランスポート

stdio

公開者

nowitsidb

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "INDIAN_MEDICINE_MCP_SERVER": {
      "command": "python",
      "args": [
        "medicines_server.py"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is INDIAN MEDICINES (MCP SERVER)?

INDIAN MEDICINES (MCP SERVER) is a comprehensive API server for medicine information lookup, alternative suggestions, and composition analysis. It provides multiple endpoints for searching, filtering, and analyzing medicine data with features like fuzzy matching and price comparison. The server is built for healthcare professionals, patients, and researchers who need quick access to Indian medicine details, alternatives, and pricing.

How to use INDIAN MEDICINES (MCP SERVER)?

Clone the repository, install dependencies from requirements.txt, prepare a JSON data file of medicines (default path /Users/siddharthbajpai/Downloads/MCP_SERVER/medicines.json), and run python medicines_server.py. Interact with the server using any MCP client, for example via MCPClient("medicines-db") and calling endpoints like search_medicines("paracetamol") or suggest_alternatives("Dolo 650").

Key features of INDIAN MEDICINES (MCP SERVER)

Exact and fuzzy name matching for medicines
Composition/ingredient-based search and analysis
Multi-criteria filtering with pagination
Alternative medicine suggestions with price comparison
Prescription requirement filtering
Performance optimizations with multiple indexing and precomputed ingredients

Use cases of INDIAN MEDICINES (MCP SERVER)

Searching for a medicine by name or ingredient to get detailed info (composition, MRP, manufacturer)
Finding cheaper alternatives to a prescribed medicine
Analyzing a composition string to extract structured ingredient data
Filtering medicines by price range, manufacturer, or prescription requirement
Obtaining statistical overview and categorization of the medicines database

FAQ from INDIAN MEDICINES (MCP SERVER)

What does the server do?

It provides a comprehensive API for searching, filtering, and analyzing Indian medicine data, including fuzzy name matching, composition analysis, and alternative suggestions with price savings.

What data does the server use?

The server loads a JSON file of medicines. The default path is /Users/siddharthbajpai/Downloads/MCP_SERVER/medicines.json. Each medicine record includes fields like Name, Manufacturer, Composition, MRP, Prescription requirement, and processed fields like Active_Ingredients and Price_Category.

How many API endpoints are available?

The server exposes 15 endpoints divided into search, filter, analysis, and utility categories. Endpoints include get_medicine_by_name, search_medicines, fuzzy_search_by_name, search_by_composition, filter_by_price_range, filter_by_manufacturer, filter_by_prescription_requirement, paginated_search, find_similar_medicines, analyze_composition, count_medicines_by_composition, categorize_medicines, and get_medicine_statistics.

What are the runtime requirements?

The server runs on Python 3.8+ and uses the FastMCP framework. Dependencies include difflib, re, collections, math, typing, and dataclasses. No authentication or special transport configuration is mentioned; it communicates via the MCP protocol.

What are the main limitations?

The server’s performance depends on the size of the JSON dataset. Fuzzy search uses a similarity threshold (default 0.6) to control result relevance, and pagination is limited by the page_size parameter. The data is local and not automatically updated.

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