dexpaprika-mcp: DexPaprika MCP server for real-time crypto token data, DEX trading activity, and DeFi analytics across

by coinpaprika · MCP Server · ★ 118

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install dexpaprika-mcp

npm install -g dexpaprika-mcp
npx dexpaprika-mcp

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 78/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

claude-integrationcrypto-analysis-toolcrypto-apicryptocurrencydefidexdexpaprikajavascriptmcpmodel-context-protocol

Quick Facts

Stars118
Forks31
LanguageJavaScript
CategoryMCP Server
LicenseMIT
Quality Score78/100
Open Issues4
Last Updated2026-11-05
Created2025-03-11
Platformsclaude-code, mcp, node
Est. Tokens~15k

About dexpaprika-mcp

DexPaprika MCP Server A Model Context Protocol (MCP) server that provides on-demand access to DexPaprika's cryptocurrency and DEX data API. Built specifically for AI assistants like Claude to programmatically fetch real-time token, pool, and DEX data with zero configuration. TL;DR DexPaprika MCP connects Claude to live DEX data across multiple blockchains. No API keys required.

Compatible Skills

These tools work well together with dexpaprika-mcp for enhanced workflows:

  • coinos-skills — semantic(0.27)+complementary+same_lang+similar_pop+shared_platform (54%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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