Goodnews MCP Server

What does “Goodnews” MCP Server do?

The Goodnews MCP Server is a straightforward implementation of the Model Context Protocol (MCP) designed to deliver curated, positive, and uplifting news stories. It acts as an intermediary between AI assistants and external news data sources, specifically fetching articles from NewsAPI and ranking them using a Cohere large language model (LLM) for positive sentiment. This enables AI-powered agents and workflows to surface feel-good news content, enhancing user interactions and providing real-time access to sentiment-filtered news. The Goodnews MCP Server exemplifies how MCP infrastructure can simplify integration with third-party APIs and LLMs, supporting developers in creating joyful, context-aware applications.

List of Prompts

No information about prompt templates is provided in the repository.

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List of Resources

No explicit resource definitions were found in the provided repository files or documentation.

List of Tools

No detailed tool descriptions or a server.py file are present in the repository structure or documentation, so tool listing is not possible based on the available information.

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Use Cases of this MCP Server

• Curated Positive News Delivery: Enables AI assistants to fetch and present users with the latest uplifting news stories, improving user mood and experience.
• Sentiment-Based Content Ranking: Uses an LLM to filter and rank news articles by positive sentiment, ensuring only the most uplifting stories are shown.
• News Aggregation for Dashboards: Integrates seamlessly into dashboards or widgets to provide a daily dose of good news, supporting corporate wellness or educational environments.
• Chatbot Integration: Powers conversational agents that can respond to user requests for good news, making interactions more engaging and optimistic.
• Content Moderation & Filtering: Assists platforms in surfacing only positive and inspiring content, helping reduce negativity in digital spaces.

How to set it up

No setup instructions or platform-specific configuration guidelines are available in the provided repository or documentation.

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:

{
  "goodnews-mcp": {
    "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 “goodnews-mcp” 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

Based on the available documentation, the MCP Goodnews server offers a clear purpose and interesting use cases, but lacks comprehensive implementation and integration details.

Our opinion

This MCP scores moderately, as it has clear utility and a permissive license, but lacks technical documentation, tool definitions, and setup guides. For developers seeking a turnkey MCP solution, more detail is needed for seamless integration.

MCP Score