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by trailofbits · MCP Server · ★ 96
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Slither MCP Server A Model Context Protocol (MCP) server that provides static analysis capabilities for Solidity smart contracts using Slither. Overview This MCP server wraps Slither static analysis functionality, making it accessible through the Model Context Protocol. It can analyze Solidity projects (Foundry, Hardhat, etc.) and generate comprehensive metadata about contracts, functions, inheritance hierarchies, and more. You can also use Slither MCP as an easy-to-use Slither API for other use cases. Features Caching: Slither runs are cached to for faster subsequent loads MCP Tools: Query contract and function information through MCP tools Security Analysis: Run Slither detectors and access results with filtering Comprehensive Analysis: Extracts detailed information about: Contract metadata (abstract, interface, library flags) Function signatures and modifiers -
| Stars | 96 |
| Forks | 10 |
| Language | Python |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 74.0273269220714/100 |
| Open Issues | 16 |
| Last Updated | 2026-05-19 |
| Created | 2025-08-25 |
| Platforms | mcp, python |
| Est. Tokens | ~175k |
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slither-mcp is MCP server for Slither static analysis of Solidity smart contracts. It is categorized as a MCP Server with 96 GitHub stars.
slither-mcp is primarily written in Python. It covers topics such as ethereum, mcp, model-context-protocol.
You can find installation instructions and usage details in the slither-mcp GitHub repository at github.com/trailofbits/slither-mcp. The project has 96 stars and 10 forks, indicating an active community.
slither-mcp is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to slither-mcp on Agent Skills Hub include Wazuh-MCP-Server, CoWork-OS, toolhive-studio. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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.
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