aport-agent-guardrails vs intent-plane

Agent action authorization projects compared

aport-agent-guardrails and intent-plane both place authorization checks between agents and actions. aport-agent-guardrails focuses on supported agent integrations and repository checks, while intent-plane centers on declared intents, signed policies, and independently verifiable decision records.

aport-agent-guardrailsintent-plane
LanguageShellGo
Stars281
Forks40
Last analyzedOct 23, 2026Nov 6, 2026

Key differences

  • aport-agent-guardrails checks supported tool calls through framework hooks, plugins, and adapters; intent-plane evaluates declared intents at the tool-call boundary, with a focus on irreversible actions.
  • aport-agent-guardrails supports local evaluation or hosted API verification; intent-plane uses signed policy artifacts and refuses requests when evaluation is uncertain.
  • aport-agent-guardrails integrates with Claude Code, Cursor, OpenClaw, LangChain, and CrewAI, among others; intent-plane offers Go and Python SDKs plus optional LangChain and MCP adapters.
  • aport-agent-guardrails is written in Shell and reports its license as NOASSERTION, while its README describes it as Apache 2.0; intent-plane is written in Go.
  • aport-agent-guardrails records allow and deny decisions and supports rollout modes; intent-plane provides durable records designed for independent recomputation with Go and Python verifier tools.
  • aport-agent-guardrails reports 27 stars and 4 forks; intent-plane reports 0 stars and 0 forks. intent-plane also describes key authority and record signing as staged or test-grade.

Choose aport-agent-guardrails if you…

  • need runtime checks across supported coding-agent tools and frameworks.
  • want to evaluate policies locally or use hosted verification, with options to audit before enforcing.
  • need a GitHub Actions workflow for repository policy checks.
Read the aport-agent-guardrails analysis →

Choose intent-plane if you…

  • need a fail-closed gate for declared intents before potentially irreversible actions.
  • want Go or Python tools to independently recompute decisions from a durable feed.
  • need derived idempotency keys to detect duplicate actions across retries and replicas.
Read the intent-plane analysis →

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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.