edwin MCP Server

What does “edwin” MCP Server do?

The “edwin” MCP (Model Context Protocol) Server is designed to connect AI assistants with external data sources, APIs, or services, enhancing development workflows by making context and actions available to LLMs. By exposing resources, tools, and prompt templates, the edwin MCP Server enables tasks such as dynamic data queries, automated file management, and seamless API interactions. This integration empowers developers to build smarter, more capable AI agents that can access relevant information, perform actions, and provide context-aware solutions. The server serves as a bridge between AI systems and the external world, streamlining processes like database management, codebase navigation, and workflow automation.

List of Prompts

No information found in the provided URL or its files.

List of Resources

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List of Tools

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Use Cases of this MCP Server

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How to set it up

Windsurf

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Claude

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Cursor

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Cline

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How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "MCP-name": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “MCP-name” to whatever the actual name of your MCP server is (e.g., “github-mcp”, “weather-api”, etc.) and replace the URL with your own MCP server URL.

Overview

Between these two tables, the edwin MCP Server repository provides only a high-level overview, without documentation or code for prompts, resources, tools, setup, or features like Roots or Sampling. Based on the available evidence, the utility for developers is highly limited at this time.

MCP Score

Overall, I would rate this MCP server a 1/10 due to the lack of accessible information, implementation details, or documentation in the provided URL. It is not possible to evaluate its utility or feature set without further access.