Provides code coverage reporting for the MCP server repository
Hosts the repository with CI/CD workflows for linting, testing, and releasing the server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Goodnews show me some uplifting news from this week"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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!
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.
Related MCP server: mcp-rss-aggregator
mcp-goodnews# Clone the repository
git clone https://github.com/VectorInstitute/mcp-goodnews.gitIn the next step, we'll need to provide the absolute path to the location of this cloned repository.
# Navigate to the configuration directory
cd ~/Library/Application\ Support/Claude/config
# Edit the claude_desktop_config.json file
nano claude_desktop_config.json# Navigate to the configuration directory
cd %APPDATA%\Claude\config
# Edit the claude_desktop_config.json file
notepad claude_desktop_config.jsonAnd you'll want to add an entry under mcpServers for Goodnews:
{
"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>"
}
}
}
}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.
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."
When you request good news, the application queries the NewsAPI for recent articles
The Cohere LLM analyzes the sentiment of each article
Articles are ranked based on positive sentiment score
The top-ranking good news stories are returned to you through Claude
Stay positive with Goodnews MCP!
Fetch a list of headlines and return only top-ranked news based on positivity.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | all |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions filtering by positivity but lacks details on permissions, rate limits, data freshness, or what 'top-ranked' entails (e.g., algorithm, recency). This leaves significant gaps for a tool that likely involves external data fetching.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for a simple tool, though it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain return values, error handling, or behavioral traits like how 'positivity' is measured, making it inadequate for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It doesn't mention the 'category' parameter at all, failing to add meaning beyond the schema. However, with only one parameter and an enum in the schema, the baseline is moderate, but the description offers no parameter context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('fetch a list of headlines') and the resource ('top-ranked news based on positivity'), making the purpose understandable. However, it doesn't differentiate from siblings since there are none, and 'top-ranked' could be more specific about ranking criteria.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, prerequisites, or contextual triggers. The description implies filtering by positivity but doesn't specify scenarios or limitations for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0fetch_list_of_goodnewsWith only one tool, there is no possibility of confusion or overlap between tools. The tool has a clear, distinct purpose focused on fetching positive news headlines.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'fetch_list_of_goodnews' follows a clear verb_noun pattern, making it predictable and readable.
A single tool is too few for a server named 'MCP Goodnews', which suggests a broader domain of positive news handling. This minimal set limits functionality and feels thin, lacking operations like filtering, searching, or managing news items.
The tool surface is severely incomplete for a news-related server. It only provides fetching of top-ranked positive news, with no ability to create, update, delete, or search news items, leaving significant gaps that could cause agent failures in broader workflows.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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