agent-bom registry

基于内置 1185 条 MCP 服务器安全元数据注册表，提供服务器查询、市场预安装信任检查、批量风险评分、Skill 文件信任评估与 Semgrep SAST 代码扫描；默认零网络、零凭据，仅可选使用 SNYK_TOKEN 做漏洞增强。

msaad00

热度 68.67

最近更新 2026-10-10 10:42:04

分类：安全依赖：MCP 服务 / 代码执行 / 读写文件 / 第三方 API应用场景：代码审查 / 报告撰写 / 研究 / DevOps

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add agent-bom-registry

Metadata

name: agent-bom-registry
description: MCP server security registry and trust assessment — look up servers in the 1185-entry server security metadata registry, run pre-install marketplace checks, batch fleet risk scoring, assess skill file trust, and run SAST code scans. Use when the user mentions MCP server trust, registry lookup, marketplace check, or skill trust assessment.
version: 0.108.4
license: Apache-2.0
compatibility: Requires Python 3.11+. Install via pipx or pip. Optional: Semgrep for SAST code scanning. No API keys or network access required (registry is bundled).
metadata: {"author":"msaad00","homepage":"https://github.com/msaad00/agent-bom","source":"https://github.com/msaad00/agent-bom","pypi":"https://pypi.org/project/agent-bom/","scorecard":"https://securityscorecards.dev/viewer/?uri=github.com/msaad00/agent-bom","tests":7239,"install":{"pipx":"agent-bom","pip":"agent-bom"},"openclaw":{"requires":{"bins":[],"env":[],"credentials":"none"},"credential_policy":"Zero credentials required. Registry data is bundled locally. No network calls needed.","credential_handling":"No credentials are required for bundled registry lookups. Optional enrichment tokens must stay in the operator environment and must not be printed or embedded in skill output.","optional_env":[{"name":"SNYK_TOKEN","purpose":"Optional third-party vulnerability enrichment for code_scan (requires SNYK_TOKEN)","required":false}],"optional_bins":["semgrep"],"emoji":"🔍","homepage":"https://github.com/msaad00/agent-bom","source":"https://github.com/msaad00/agent-bom","license":"Apache-2.0","os":["darwin","linux","windows"],"data_flow":"Purely local. Registry data (1185 MCP server metadata records) is bundled in the package. Lookups are in-memory string matches. Skill trust analysis parses user-provided SKILL.md content passed as a string argument.","file_reads":["user-provided SKILL.md files (for skill_trust analysis)"],"file_writes":[],"network_endpoints":[{"url":"https://api.snyk.io","purpose":"Optional third-party vulnerability enrichment for code_scan (requires SNYK_TOKEN)","auth":true}],"telemetry":false,"persistence":false,"privilege_escalation":false,"always":false,"autonomous_invocation":"restricted"}}

agent-bom-registry — MCP Server Trust & Security Registry

Look up MCP servers in the 1185-entry server security metadata registry, assess skill file trust, and run pre-install marketplace checks.

Install

pipx install agent-bom
agent-bom mcp scan @modelcontextprotocol/server-brave-search --ecosystem npm
agent-bom mcp scan @modelcontextprotocol/server-filesystem --ecosystem npm

Tools (7)

Tool	Description
`registry_lookup`	Look up MCP server in the 1185-entry security metadata registry
`marketplace_check`	Pre-install trust check with registry cross-reference
`fleet_scan`	Batch registry lookup + risk scoring for MCP server inventories
`skill_scan`	Scan instruction files for package refs, trust, and findings
`skill_verify`	Verify Sigstore provenance for instruction files
`skill_trust`	Assess skill file trust level (5-category analysis)
`code_scan`	SAST scanning via Semgrep with CWE-based compliance mapping

Example Workflows

# Look up a server in the registry
registry_lookup(server_name="brave-search")

# Pre-install trust check
marketplace_check(package="@modelcontextprotocol/server-filesystem")

# Scan instruction files and then assess a specific skill file
skill_scan(path=".")
skill_trust(skill_path="./SKILL.md")

# Batch risk scoring
fleet_scan(servers=["brave-search", "github", "slack"])

MCP Resources

Resource	Description
`registry://servers`	Browse the 1185-entry MCP server security metadata registry

Privacy & Data Handling

Registry data is bundled in the package — lookups are in-memory string matches with zero network calls. Skill trust analysis parses content passed as a string argument (no file system access needed).

Verification

Source: github.com/msaad00/agent-bom (Apache-2.0)
7,100+ tests with CodeQL + OpenSSF Scorecard
No telemetry: Zero tracking, zero analytics