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INDIAN MEDICINES (MCP SERVER)

@nowitsidb

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.
Overview

What is INDIAN MEDICINE (MCP SERVER)?

INDIAN MEDICINE (MCP SERVER) is a comprehensive API server designed for medicine information lookup, alternative suggestions, and composition analysis. It provides multiple endpoints for searching, filtering, and analyzing medicine data with advanced features like fuzzy matching and price comparison.

How to use INDIAN MEDICINE (MCP SERVER)?

To use the server, clone the repository, install the dependencies, prepare your medicine database, and run the server. You can interact with the server using any MCP client to access its various API endpoints.

Key features of INDIAN MEDICINE (MCP SERVER)?

  • Advanced search capabilities with exact and fuzzy name matching.
  • Composition-based search and multi-criteria filtering.
  • Analysis tools for composition parsing and statistical analysis.
  • Medical decision support with alternative suggestions and price comparisons.
  • Performance optimizations for fast lookups and efficient calculations.

Use cases of INDIAN MEDICINE (MCP SERVER)?

  1. Searching for specific medicines by name or composition.
  2. Finding alternative medicines based on composition similarity.
  3. Analyzing the composition of medicines for ingredient extraction.
  4. Filtering medicines by price range or manufacturer.

FAQ from INDIAN MEDICINE (MCP SERVER)?

  • Can I use this API for all types of medicines?

Yes! The API covers a wide range of medicines and provides detailed information.

  • Is there a limit on the number of API calls?

The API does not impose strict limits, but it is recommended to use it responsibly to avoid overloading the server.

  • How can I contribute to the project?

Contributions are welcome! You can fork the repository, create a feature branch, and submit a pull request.

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