Sephera — security grade SAFE, quality 68/100

Security audit verdict: SAFE · quality 68/100

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 Reim-developer · MCP Server · ★ 77

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

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About Sephera

Sephera Sephera is a Rust CLI for understanding codebases fast. Count a repository, build a deterministic AI-ready context pack, trace dependency blast radius, or expose the same workflows through MCP from one binary. Documentation: Current release line: (pre-1.0). Sephera currently focuses on four practical commands: : fast, language-aware line counting across project trees : deterministic Markdown or JSON bundles with AST compression, focus paths, and Git diff awareness : dependency graph analysis via Tree-sitter import extraction : built-in MCP server for direct AI agent integration It is intentionally narrow in scope. Sephera does not try to be an agent runtime, a hosted service, or a provider-specific AI wrapper. New in : URL mode for , , and , including GitHub/GitLab tree URLs, remote config discovery, and MCP support. Why Sephera Most codebase tools stop at one layer: metrics tools

ai-toolsclicli-toolscode-analysiscontext-engineeringdependency-graphdeveloper-toolsllmmcprefactoring

Quick Facts

Stars77
Forks9
LanguageRust
CategoryMCP Server
LicenseGPL-3.0
Quality Score67.7336193265984/100
Last Updated2026-10-10
Created2025-04-11
Platformscli, mcp, rust
Est. Tokens~25k

Sephera alternative? Top 6 similar tools

Looking for a Sephera alternative? If you're comparing Sephera with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • logicstamp-context by LogicStamp · ⭐ 84

    A Context Compiler for TypeScript. Deterministic, diffable architectural contracts and dependency graphs for A

  • fossil-mcp by yfedoseev · ⭐ 68

    The code quality toolkit for the agentic AI era. Find dead code, clones, and scaffolding across 15 languages.

  • arbor by Anandb71 · ⭐ 160

    Graph-native code intelligence that replaces embedding-based RAG with deterministic program understanding.

  • ops-codegraph-tool by optave · ⭐ 98

    Code intelligence CLI — function-level dependency graph across 34 languages, 34-tool MCP server for AI agents,

  • stacklit by glincker · ⭐ 101

    One command gives AI agents instant codebase context. ~250 tokens replaces 50,000+ tokens of exploration. Auto

  • CodeMCP by SimplyLiz · ⭐ 90

    Code intelligence for AI assistants - MCP server, CLI, and HTTP API with symbol navigation, impact analysis, a

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Frequently Asked Questions

What is Sephera?

Sephera is Answer "what breaks if I change this?" Reverse dependency analysis, cycle detection, and token-budgeted context packs. Rust CLI with built-in MCP server.. It is categorized as a MCP Server with 77 GitHub stars.

What programming language is Sephera written in?

Sephera is primarily written in Rust. It covers topics such as ai-tools, cli, cli-tools.

How do I install or use Sephera?

You can find installation instructions and usage details in the Sephera GitHub repository at github.com/Reim-developer/Sephera. The project has 77 stars and 9 forks, indicating an active community.

What license does Sephera use?

Sephera is released under the GPL-3.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to Sephera?

The top alternatives to Sephera on Agent Skills Hub include logicstamp-context, fossil-mcp, arbor. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

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