Web Search MCP Server with ChromaDB Vector Database

Created By
joao-santilloa year ago
Servidor MCP que busca documentação mais atualizada de tools
Overview

What is Web Search MCP Server?

Web Search MCP Server is a server that provides tools for web search and vector database functionality using LangChain and ChromaDB, allowing users to search for documentation and manage vector embeddings.

How to use Web Search MCP Server?

To use the server, install the required dependencies, set up a .env file with necessary configurations, and run the server using the command python main.py.

Key features of Web Search MCP Server?

  • Search documentation for popular libraries like LangChain and OpenAI.
  • Extract content from web pages.
  • Store and retrieve documents with vector embeddings using ChromaDB.
  • Perform semantic similarity searches and filter documents based on metadata.
  • Support for batch operations for efficiency.

Use cases of Web Search MCP Server?

  1. Searching for documentation on specific libraries.
  2. Managing and retrieving documents in a vector database.
  3. Performing semantic searches to find related content.

FAQ from Web Search MCP Server?

  • What libraries can I search documentation for?

You can search documentation for libraries such as LangChain, LlamaIndex, and OpenAI.

  • Is there a specific setup required?

Yes, you need to create a .env file with API keys and configurations before running the server.

  • Can I perform batch operations?

Yes, the server supports batch operations for adding multiple documents to the vector database.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
joao-santillo
Star
0
Language
Python
License
-

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