microsoft/markitdown
MarkItDown is a Python tool that converts various file formats into Markdown and integrates with LLM applications via an MCP server for enhanced text analysis and document processing.
Awesome MCP › Other MCP Servers
Bing Search MCP Server connects MCP-compatible assistants to the Microsoft Bing Search API so a model can look things up on the web during a conversation. Three tools are documented. The web search tool runs a general query and accepts a result count, an offset for paging through results, and a market code that defaults to United States English. The news search tool retrieves articles and current events with the same count and market parameters plus a freshness parameter, defaulting to the last day, that limits how recent the results must be. The image search tool returns visual results for a query with count and market parameters. Beyond the tools themselves the README lists rate limiting to avoid abusing the upstream API quota, and error handling across the three search paths. Requirements are Python 3.10 or later, a Bing Search API key, and an MCP-compatible client; Claude Desktop and Cursor are named as examples. Installation is from a clone of the repository using uv to create a virtual environment and install the package in editable mode, after which the server runs through uvx. Two environment variables configure it: the API key, which is required, and an optional endpoint URL that defaults to the public Bing endpoint, with the README giving both shell and Windows command prompt forms. Registration with Claude Desktop is shown as a JSON block naming the command, the path to the checkout, and the API key passed in the environment, with the configuration file location given for macOS and Windows. The README also links Smithery for automated installation and walks through obtaining a key by creating a Bing Search resource in the Azure portal. Released under the MIT licence.
https://github.com/leehanchung/bing-search-mcp
MarkItDown is a Python tool that converts various file formats into Markdown and integrates with LLM applications via an MCP server for enhanced text analysis and document processing.
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