by PentHertz · MCP Server · ★ 180
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Grimoire Offensive knowledge, offline. One search box for every playbook. by Penthertz - part of the RF-Swift toolkit Grimoire clones a curated set of security knowledge bases, indexes all of their markdown/YAML into a single full-text search index, and serves a fast web UI. Type , , , , , , ... and it instantly surfaces the matching pages across every source - HackTricks, PayloadsAllTheThings, the OWASP guides, the living-off-the-land databases, and your own notes - with a link back to each original. Built to run anywhere (single Python script, no mandatory services) and to be embedded in RF-Swift. Features Unified search over 20+ sources via SQLite FTS5 with BM25 ranking - one query language regardless of how each repo is authored (mdBook, mkdocs, Jekyll, Hugo, plain markdown, YAML). Fully offline once fetched. No telemetry, no external calls at runtime. Spawnable web service - (bind host/port; run it in the background or as a container service). Provenance - every doc shows its source and a link to the original file on GitHub, so you always know where guidance came from. R
| Stars | 180 |
| Forks | 20 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72.4917333500265/100 |
| Open Issues | 2 |
| Last Updated | 2026-07-01 |
| Created | 2026-06-12 |
| Platforms | mcp, python |
| Est. Tokens | ~16k |
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grimoire is Offensive knowledge, offline. One search box for every playbook.. It is categorized as a MCP Server with 180 GitHub stars.
grimoire is primarily written in Python. It covers topics such as ble, bluetooth, documentation.
You can find installation instructions and usage details in the grimoire GitHub repository at github.com/PentHertz/grimoire. The project has 180 stars and 20 forks, indicating an active community.
grimoire is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to grimoire on Agent Skills Hub include docfork, utcp-specification, Awareness-Local. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.