Artemis▌
by artemis-xyz
Artemis: Connect to the Artemis API to build and manage crypto data-analysis formulas for price, fees, revenue and time-
Integrates with Artemis API to create and manage cryptocurrency data analysis formulas for accessing price data, fees, revenue, and other time-series metrics without switching contexts.
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best for
- / Crypto traders analyzing market trends
- / DeFi researchers studying protocol metrics
- / Blockchain analysts building reports
capabilities
- / Create cryptocurrency data analysis formulas
- / Access real-time and historical price data
- / Query blockchain fee and revenue metrics
- / Manage time-series cryptocurrency datasets
- / Retrieve DeFi protocol analytics
what it does
Connects to Artemis API to create and manage cryptocurrency data analysis formulas for price data, fees, revenue, and other blockchain metrics.
about
Artemis is an official MCP server published by artemis-xyz that provides AI assistants with tools and capabilities via the Model Context Protocol. Artemis: Connect to the Artemis API to build and manage crypto data-analysis formulas for price, fees, revenue and time- It is categorized under finance, analytics data.
how to install
You can install Artemis in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Artemis is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
README content is unavailable from source data for this server.
Open GitHub repositoryFAQ
- What is the Artemis MCP server?
- Artemis is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Artemis?
- This profile displays 43 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★43 reviews- ★★★★★William Perez· Dec 24, 2024
According to our notes, Artemis benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Michael Verma· Dec 4, 2024
Artemis is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Rahul Santra· Nov 23, 2024
Artemis reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Ava Reddy· Nov 23, 2024
Artemis is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★William Li· Nov 15, 2024
Artemis has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Anika Malhotra· Nov 11, 2024
Artemis is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Pratham Ware· Oct 14, 2024
We wired Artemis into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Evelyn Garcia· Oct 14, 2024
According to our notes, Artemis benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Liam Martin· Oct 6, 2024
Artemis is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Noah Gupta· Oct 2, 2024
Artemis has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
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