toolkit: Agentic tooling for Sentry

by getsentry · MCP Server · ★ 938

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

Security audit verdict: SAFE · quality 63/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentic-workflowclimcp-servertag-production

Quick Facts

Stars938
Forks166
LanguageTypeScript
CategoryMCP Server
Quality Score63/100
Open Issues161
Last Updated2026-10-22
Created2025-03-29
Platformscli, mcp, node
Est. Tokens~16k

About toolkit

sentry-mcp Sentry's MCP service is primarily designed for human-in-the-loop coding agents. Our tool selection and priorities are focused on developer workflows and debugging use cases, rather than providing a general-purpose MCP server for all Sentry functionality.

Compatible Skills

These tools work well together with toolkit for enhanced workflows:

  • mcp-server-asana — semantic(0.50)+shared_fw(anthropic)+same_lang+similar_pop+shared_platform (60%)
  • mcp-server-cloudflare — semantic(0.50)+shared_fw(cloudflare)+same_lang+similar_pop+shared_platform (60%)
  • railway-skills — semantic(0.24)+complementary+shared_fw(anthropic,openai)+similar_pop (59%)

toolkit alternative? Top 6 similar tools

Looking for a toolkit alternative? If you're comparing toolkit 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.

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  • cupertino by mihaelamj · ⭐ 841

    A local Apple Documentation crawler and MCP server. Written in Swift.

  • Wax by christopherkarani · ⭐ 801

    Shared Single-file memory layer for all your agents, sub mili-second RAG over text, photo and video on Apple S

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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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