About
This MCP server fetches the latest cryptocurrency news and media from CryptoPanic, providing AI agents with up‑to‑date market insights. It offers a single tool to retrieve news headlines across multiple pages.
Capabilities
The cryptopanic-mcp-server bridges the gap between AI assistants and real‑time cryptocurrency news. By leveraging CryptoPanic’s comprehensive API, it delivers up‑to‑date headlines and media coverage directly to an assistant’s workflow. Developers can enrich conversational agents with market insights, regulatory updates, or sentiment trends without building a custom news crawler. The server’s single, well‑defined tool——encapsulates all external calls, ensuring that the assistant’s code remains clean and focused on higher‑level reasoning.
The tool accepts two parameters: , which selects between “news” and “media”, and , controlling how many pages of results to fetch (up to ten). Internally, the server translates these arguments into CryptoPanic API requests and formats the response as a plain‑text list. This simplicity allows an assistant to ask for “the latest Bitcoin news” or “top media stories about Ethereum” and receive a ready‑to‑display summary. Because the output is plain text, it can be fed directly into prompts or used as a basis for further NLP processing.
Key capabilities include:
- Real‑time data – Pulls the freshest headlines as soon as they appear on CryptoPanic, keeping agents informed of market movements.
- Flexible content types – Supports both traditional news articles and media‑centric pieces, enabling broader coverage.
- Pagination control – Lets developers balance detail and latency by specifying how many pages to retrieve.
- Secure integration – Requires only an API key and plan, which are injected via environment variables, keeping credentials out of code.
Typical use cases span a wide range: financial advisors querying market sentiment before advising clients; trading bots generating contextual alerts; educational agents summarizing crypto trends for students. In a conversational setting, an assistant can answer “What’s happening in the crypto market today?” by invoking , then weave those headlines into a broader analysis or risk assessment.
Integration with AI workflows is straightforward. The MCP server exposes the tool through the standard Model Context Protocol interface, so any Claude‑compatible client can request it without modification. The assistant simply calls the tool, receives a text list, and incorporates it into its response generation pipeline. This decoupling of data retrieval from reasoning means developers can focus on building smarter dialogue logic while the server handles external API orchestration.
What sets this MCP apart is its minimalism combined with real‑time relevance. A single, purpose‑built endpoint delivers high‑quality crypto news without the overhead of maintaining a custom scraper or handling pagination logic manually. For developers building AI agents that need timely market intelligence, the cryptopanic‑mcp-server offers a plug‑and‑play solution that scales with the volatility of the crypto ecosystem.
Related Servers
n8n
Self‑hosted, code‑first workflow automation platform
FastMCP
TypeScript framework for rapid MCP server development
Activepieces
Open-source AI automation platform for building and deploying extensible workflows
MaxKB
Enterprise‑grade AI agent platform with RAG and workflow orchestration.
Filestash
Web‑based file manager for any storage backend
MCP for Beginners
Learn Model Context Protocol with hands‑on examples
Weekly Views
Server Health
Information
Explore More Servers
DuckDuckGo Search MCP Server
Fast, privacy‑focused web search via MCP
Sequential Thinking MCP Server
Structured step‑by‑step problem solving for AI
Mcptools CLI
Command‑line interface for MCP servers via stdio or HTTP
RR MCP Server for .NET Analysis
Extract .NET interfaces, models, enums and OpenAPI data for AI
Mcp Server Memory
In‑memory MCP server with SSE transport for rapid prototyping
N8N MCP Server
Validate, manage, and integrate n8n workflows effortlessly