No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by bgauryy · MCP Server · ★ 945
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is octocode safe to install? View the security audit →
Octocode: Research Driven Development for AI Research like a Senior Staff Engineer.In every codebase, in seconds. Stop guessing. Octocode researches code locally and externally: your own workspace (ripgrep + LSP-level go-to-definition, references, call hierarchy) and the world's (GitHub repos, PRs, npm/PyPI packages), turning it into verifiable evidence your AI can search, read, and trace. Use it as an MCP server inside your AI assistant, or as a terminal CLI. octocode.ai · MCP Server · CLI · Skills Two ways to run Octocode Quick scripted lookups, CI, piping to othe
| Stars | 945 |
| Forks | 78 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 67.3256872312438/100 |
| Open Issues | 5 |
| Last Updated | 2026-09-27 |
| Created | 2025-06-05 |
| Platforms | claude-code, cli, mcp, node |
| Est. Tokens | ~17k |
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octocode is Code research platform for AI agents; find, understand, and prove context across your code and all of GitHub, in a fraction of the tokens. One toolset, MCP or CLI. It is categorized as a MCP Server with 945 GitHub stars.
octocode is primarily written in TypeScript. It covers topics such as agent, ai, ai-agents.
You can find installation instructions and usage details in the octocode GitHub repository at github.com/bgauryy/octocode. The project has 945 stars and 78 forks, indicating an active community.
octocode is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to octocode on Agent Skills Hub include octocode, OpenContext, atlassian-mcp-server. 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.
Sources & who's responsible: