OpenAPPA
OpenAPPA is an open, vendor-agnostic, MIT-licensed deterministic AI guardrail engine designed to prevent data exfiltration from LLM agents by tracking data flows and enforcing algebraic security labels without breaking agent utility.
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Best for: Software & Gaming
What it does
Security software for decision-makers comparing workflow fit and alternatives.
Best fit
Software & Gaming
Pricing snapshot
Pricing available on request
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OpenAPPA is a deterministic guardrail engine for AI agents that prevents data exfiltration from prompt injection or model hallucination by tracking data flows rather than relying on probabilistic classifiers or pattern blacklists. It runs outside the agent's prompt and execution loop so the model cannot see or manipulate it, and is configured via a single, declarative configuration (appa.toml) that describes data sources, audiences, trust levels, and authorities. The system produces algebraic security labels (audience × trust) that only become more restrictive as data flows, enabling validation in CI/CD and scalable application across many agents. OpenAPPA is open-source, vendor-agnostic, and MIT-licensed.
An information-flow policy engine for LLM agents.
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Claim this listing for $29Key Features
Deterministic flow-based guardrails
Tracks data flows and derives decisions algebraically using security labels (audience × trust) rather than pattern matching or probabilistic classifiers.
Runs outside agent prompt loop
Operates externally to the model's prompt and execution loop so the model cannot see, negotiate with, or manipulate the guardrail logic.
Declarative configuration (appa.toml)
Single configuration file describes tools, data sources, audiences, trust levels, and authorities; configuration can be validated in CI/CD.
Machine-readable remedy plans
Instead of outright blocking, OpenAPPA returns remedy plans with allowed ways to proceed (sanitizers, authorities, subagents) to preserve agent utility.
Sanitizers and custom plugins
Stock sanitizers ship with the system and custom sanitizers (including model-based ones) can be plugged in with constrained blast radii to transform or redact payloads.
Authorities and subagents
Authorities can approve specific actions without lifting session restrictions broadly; subagents isolate untrusted reads in disposable branches to avoid poisoning the parent trajectory.
Cross-platform, pluggable engine
Designed to plug into existing agent loops in one place and work across platforms and deployment models.
Open-source, MIT license
The project is open and MIT-licensed, and positioned as vendor-agnostic.
Pricing
OpenAPPA is MIT-licensed open source (no paid tiers specified on the page).
Use Cases
Securing coding agents
Prevent sensitive data leaks and ensure safe tool usage for agents that perform code or automation tasks.
LLM proxies and gateways
Deploy as a protective layer for LLM proxies, MCP gateways, and MCP servers to enforce data-flow-based policies across tool calls.
Agents in production
Enable deterministic guardrails that scale across many agents while validating policy coverage in CI/CD without breaking agent task completion.
Compliance and auditing
Declarative configurations and algebraic labels allow auditable policies and verifiable coverage of tool graphs.
Fallback and remediation workflows
Provide machine-readable remedies such as sanitization, authority approvals, or subagent isolation instead of hard blocking to preserve utility.
Integrations
LLM proxies / MCP gateways / MCP servers
Intended to be deployed alongside or in front of LLM proxies, gateways, and MCP servers to enforce flow-based policies.
Coding agents / agent frameworks
Designed to plug into coding agents and agent loops to control tool calls and data flow without breaking agent behavior.
Benefits
Limitations
No verified limitations are available.
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Read the documentation and 'Get started' materials on the OpenAPPA site
- 2 Add OpenAPPA to your agent loop (the engine plugs into an existing agent loop in one place)
- 3 Create and configure appa.toml to describe tools, data sources, audiences, trust levels, and authorities
- 4 Use supplied sanitizers or plug in custom sanitizers and authorities as needed
- 5 Validate the declarative configuration in CI/CD to ensure your tool graph is covered
Support
docs
Documentation and 'Get started' pages available on the OpenAPPA website.
community
Discord and GitHub links are available from the site for community support and project source.
API
Documentation and usage examples (site provides docs and mentions usage 'as MCP server' and 'as curl') available from the main site
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