MCP Goodnews logo

MCP Goodnews

Organization
VectorInstitute

A simple MCP application that delivers curated positive and uplifting news stories.

PublisherVectorInstitute
Repositorymcp-goodnews
LanguagePython
Forks
10
Stars
47
Available tools
0
Transport typestdio
Categories
LicenseApache-2.0
Links
  • Connect tools to AI workflows

    MCP Goodnews exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    47 stars and 10 forks from the linked repository.

MseeP.ai Security Assessment Badge

MCP Goodnews


CodeQL Linting Unit Testing and Upload Coverage codecov Release GitHub License

MCP Goodnews is a simple Model Context Protocol (MCP) application that features a server for getting good, positive, and uplifting news. This tool fetches news articles from the NewsAPI and uses a Cohere LLM to rank and return the top news articles based on positive sentiment.

Read the blog post on Medium!

Motivation

In a world where negative news often dominates headlines, Goodnews MCP aims to shine a light on more positive and uplifting news stories. This project was inspired by an earlier initiative called GoodnewsFirst, which delivered positive news daily to email subscribers — it was a really awesome project! While GoodnewsFirst predated recent breakthroughs in Large Language Models (LLMs) and relied on traditional methods for sentiment ranking, Goodnews MCP leverages modern LLMs to perform sentiment analysis in a zero-shot setting.

Example Usage: MCP Goodnews with Claude Desktop

Requirements

Clone mcp-goodnews

bash
# Clone the repository
git clone https://github.com/VectorInstitute/mcp-goodnews.git

In the next step, we'll need to provide the absolute path to the location of this cloned repository.

Update Claude Desktop Config to find mcp-goodnews

For Mac/Linux

bash
# Navigate to the configuration directory
cd ~/Library/Application\ Support/Claude/config

# Edit the claude_desktop_config.json file
nano claude_desktop_config.json

For Windows

bash
# Navigate to the configuration directory
cd %APPDATA%\Claude\config

# Edit the claude_desktop_config.json file
notepad claude_desktop_config.json

And you'll want to add an entry under mcpServers for Goodnews:

json
{
  "mcpServers": {
    "Goodnews": {
      "command": "<absolute-path-to-bin>/uv",
      "args": [
        "--directory",
        "<absolute-path-to-cloned-repo>/mcp-goodnews/src/mcp_goodnews",
        "run",
        "server.py"
      ],
      "env": {
        "NEWS_API_KEY": "<newsapi-api-key>",
        "COHERE_API_KEY": "<cohere-api-key>"
      }
    }
  }
}

Start or Restart Claude Desktop

Claude Desktop will use the updated config to build and run the mcp-goodnews server. If successful, you will see the hammer tool in the bottom-right corner of the chat dialogue window.

Clicking the hammer tool icon will bring up a modal that lists available MCP tools. You should see fetch_list_of_goodnews listed there.

Ask Claude for Good News

Example prompts:

  • "Show me some good news from today."
  • "What positive things happened in the world this week?"
  • "Give me uplifting news stories about science."

How It Works

  1. When you request good news, the application queries the NewsAPI for recent articles
  2. The Cohere LLM analyzes the sentiment of each article
  3. Articles are ranked based on positive sentiment score
  4. The top-ranking good news stories are returned to you through Claude

License

Apache 2.0


Stay positive with Goodnews MCP!

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "vectorinstitute-mcp-goodnews": {
      "command": "",
      "args": []
    }
  }
}

Use MCP Goodnews MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once MCP Goodnews is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add MCP Goodnews as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the MCP Goodnews MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "vectorinstitute-mcp-goodnews": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-goodnews"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the MCP Goodnews MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the MCP Goodnews MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use MCP Goodnews to help me with this task?
MCP Goodnews
Sure. I read it.
Here is what I found using MCP Goodnews.

Frequently asked questions

What is the MCP Goodnews MCP server used for?

MCP Goodnews is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use MCP Goodnews MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use MCP Goodnews with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use MCP Goodnews MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With MCP Goodnews connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect MCP Goodnews MCP to TypingMind?

MCP Goodnews runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does MCP Goodnews MCP provide in TypingMind?

MCP Goodnews exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use MCP Goodnews MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If MCP Goodnews requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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