web3-research-mcp: Local MCP server for deep crypto token research across CoinGecko, DeFiLlama and web search. Free, no API key

by aaronjmars · MCP Server · ★ 168

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

How to install web3-research-mcp

npx -y @smithery/cli install web3-research-mcp --client claude

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 74/100

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. Full audit →

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.

claudecoingeckocryptodefillamamcpmcp-cryptomcp-servermodel-context-protocoltypescriptweb3

Quick Facts

Stars168
Forks56
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score74/100
Last Updated2026-10-22
Created2025-04-11
Platformsbrowser, claude-code, mcp, node
Est. Tokens~15k

About web3-research-mcp

Web3 Research MCP Deep Research for crypto - free & fully local 🧠 🚀 Preview 🧠 Features Comprehensive Research: Gather detailed information about any cryptocurrency token Multi-Source Analysis: Research across multiple sources including CoinGecko, CoinMarketCap, DeFiLlama, and more Structured Reporting: Generate detailed reports covering technical fundamentals, market data, social sentiment,...

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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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