faramesh-core — security grade SAFE, quality 66/100

Security audit verdict: SAFE · quality 66/100

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 faramesh · MCP Server · ★ 100

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

🔒 Is faramesh-core safe to install? View the security audit →

About faramesh-core

Every agent tool call is a policy decision. Declare permissions in . A local daemon permits, defers, or denies each tool call before it runs. Decisions are hash-chained in a WAL. No SDK lock-in. No cloud required. <img alt="Quickstart" src="https://img.s

agent-governanceagent-governance-toolkitagent-runtimeagent-securityagentic-aiai-agentsautogencrewaideterministicdeterministic-ai

Quick Facts

Stars100
Forks19
LanguageGo
CategoryMCP Server
LicenseApache-2.0
Quality Score66.1214279963307/100
Open Issues10
Last Updated2026-07-21
Created2026-01-14
Platformsgo, mcp
Est. Tokens~16k

Compatible Skills

These tools work well together with faramesh-core for enhanced workflows:

  • kube-agentic-networking — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (52%)
  • DashClaw — semantic(0.24)+complementary+rare_topics+similar_pop (52%)

faramesh-core alternative? Top 6 similar tools

Looking for a faramesh-core alternative? If you're comparing faramesh-core 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.

  • Sponsio by SponsioLabs · ⭐ 440

    Deterministic safety solutions for probabilistic AI agents

  • DashClaw by ucsandman · ⭐ 306

    Remote approvals, policy checks, and execution evidence for unattended AI agents.

  • oreilly-ai-agents by sinanuozdemir · ⭐ 299

    An introduction to the world of AI Agents

  • eval-view by hidai25 · ⭐ 133

    Regression testing for AI agents. Snapshot behavior,diff tool calls,catch regressions in CI. Works with LangGr

  • agents-shipgate by ThreeMoonsLab · ⭐ 89

    The deterministic merge gate for AI-generated agent capability changes — a local-first, static Tool-Use Readin

  • Agent-Wiz by Repello-AI · ⭐ 385

    A CLI tool for threat modeling and visualizing AI agents built using popular frameworks like LangGraph, AutoGe

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Frequently Asked Questions

What is faramesh-core?

faramesh-core is Governance-as-Code for AI agents. Declarative constraints with deterministic enforcement. Provisioning Identity, Tool-based rules, Brokering Credentials & Ensuring safe deployment. It is categorized as a MCP Server with 100 GitHub stars.

What programming language is faramesh-core written in?

faramesh-core is primarily written in Go. It covers topics such as agent-governance, agent-governance-toolkit, agent-runtime.

How do I install or use faramesh-core?

You can find installation instructions and usage details in the faramesh-core GitHub repository at github.com/faramesh/faramesh-core. The project has 100 stars and 19 forks, indicating an active community.

What license does faramesh-core use?

faramesh-core is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to faramesh-core?

The top alternatives to faramesh-core on Agent Skills Hub include Sponsio, DashClaw, oreilly-ai-agents. 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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