coindesk-mcp
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
The two tools have clearly distinct purposes: read_news extracts full content from a specific article URL, while recent_news fetches a list of recent articles from an RSS feed. There is no overlap in functionality, and an agent can easily distinguish between retrieving a single article versus getting multiple recent articles.
Naming Consistency5/5Both tools follow a consistent verb_noun pattern (read_news and recent_news) with clear, descriptive names. The naming convention is uniform throughout the tool set, making it predictable and easy for agents to understand.
Tool Count2/5With only 2 tools, the server feels thin for a news domain. While the tools cover reading specific articles and listing recent ones, there are likely gaps such as searching news, filtering by category, or accessing historical archives. The count is too low for comprehensive news interaction.
Completeness2/5The tool surface is significantly incomplete for a news server. It lacks essential operations like searching for articles by keyword, filtering by date or category, and accessing older or archived news. Agents will struggle with basic news-related tasks beyond the two provided functions.
Average 4.3/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
This server has been verified by its author.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing key behaviors: it fetches HTML content, processes it for structured extraction, and mentions potential error conditions (HTTPStatusError, parsing errors). It doesn't cover rate limits, caching behavior, or authentication requirements, but provides solid operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, args, returns, raises) and front-loaded key information. Some sentences could be more concise (e.g., 'Fetches the HTML content from the provided URL, processes it to extract structured news information' could be tightened), but overall it's efficient and organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no annotations and no output schema, the description provides good completeness: clear purpose, parameter explanation, return format description, and error conditions. It could benefit from more explicit sibling tool differentiation and operational constraints, but covers the essential context well.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and only one parameter, the description fully compensates by clearly explaining the 'url' parameter's purpose ('complete URL of the CoinDesk news article to retrieve') and constraints. It adds essential meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('retrieves and extracts full content'), resource ('news article from CoinDesk'), and scope ('structured news information including title, subtitle, author, publication date, and article content'). It distinguishes from the sibling tool 'recent_news' by focusing on individual article extraction rather than recent news listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the mention of 'CoinDesk news article' and the required URL parameter, but doesn't explicitly state when to use this tool versus the 'recent_news' sibling. No explicit guidance on prerequisites, alternatives, or exclusion criteria is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: fetching and parsing an RSS feed, returning formatted news items, and raising specific errors (HTTPStatusError, Exception). This covers key operational aspects like data source, processing steps, and error handling, though it lacks details on rate limits or caching.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose in the first sentence. Subsequent sentences add necessary details about the process, return format, and error handling without redundancy. It could be slightly more concise by combining some sentences, but overall it is efficient and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (fetching and parsing external data) and lack of annotations or output schema, the description provides a complete picture: it explains what the tool does, how it works, the return format, and potential errors. This is sufficient for an agent to understand and use the tool effectively, though an output schema would further enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so no parameter information is needed. The description appropriately does not discuss parameters, focusing instead on the tool's functionality and output. This meets the baseline for tools with no parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('retrieves'), resource ('latest cryptocurrency and blockchain news articles'), and source ('from CoinDesk's RSS feed'). It distinguishes from the sibling tool 'read_news' by specifying the RSS feed source and real-time nature ('latest'), whereas 'read_news' might imply reading stored or different news sources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'latest' news and the CoinDesk source, which helps differentiate from 'read_news'. However, it does not explicitly state when to use this tool versus 'read_news' or provide any exclusions or prerequisites for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/narumiruna/coindesk-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server