Goodnews MCP Server
Surface feel-good news in your workflows: Goodnews MCP fetches and ranks positive stories, helping AI agents and dashboards elevate user mood with curated uplifting content.
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.
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.
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
| Section | Availability | Details/Notes |
|---|---|---|
| Overview | ✅ | Overview provided in README.md |
| List of Prompts | ⛔ | No prompt templates documented |
| List of Resources | ⛔ | No MCP resources documented |
| List of Tools | ⛔ | No tool list or server.py present |
| Securing API Keys | ⛔ | Not addressed in available documentation |
| Sampling Support (less important in evaluation) | ⛔ | No evidence of sampling support |
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
| Has a LICENSE | ✅ (Apache-2.0) |
|---|---|
| Has at least one tool | ⛔ |
| Number of Forks | 5 |
| Number of Stars | 39 |
Frequently asked questions
- What is the Goodnews MCP Server?
The Goodnews MCP Server is a Model Context Protocol implementation designed to fetch and deliver curated, positive news stories. It uses NewsAPI as a data source and a Cohere LLM to rank articles by positive sentiment, enabling AI agents and dashboards to surface uplifting content.
- How does the Goodnews MCP Server filter news?
It queries NewsAPI for the latest articles, then uses a large language model to evaluate and rank these stories based on their positive sentiment before returning them through the MCP interface.
- What are common use cases for Goodnews MCP?
Typical use cases include powering chatbot responses with good news, embedding uplifting content in dashboards, supporting corporate wellness, and filtering news feeds to show only positive stories.
- Is the Goodnews MCP Server open source?
Yes, it is released under the Apache-2.0 license, making it freely usable and modifiable for your projects.
- Does Goodnews MCP provide prompt templates or explicit tool definitions?
No prompt templates or explicit tool/resource definitions are provided in the available documentation. The server’s primary function is to fetch and rank news for positive sentiment.
- How do I integrate Goodnews MCP in FlowHunt?
Add the MCP component to your FlowHunt flow, and configure it with your Goodnews MCP server details in JSON format. Once set up, your AI agent can access the server to fetch and deliver positive news.
- Are there setup instructions or API key guidelines?
Specific setup instructions and API key management are not included in the available documentation. You will need to refer to NewsAPI and Cohere documentation for API key handling as needed.
Try Goodnews MCP Server on FlowHunt
Integrate uplifting news delivery into your AI flows and chatbots. Discover how Goodnews MCP can maximize positive user engagement in minutes.
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