Invariant Guardrails
https://invariantlabs.ai/blog/guardrails
Contextual guardrailing layer for agentic and MCP applications that sits at the LLM and MCP level. It enforces deterministic rules over tool calls, data flow, secrets, PII, code and loops.
Acquired · Verified 2026-10-29 · fresh as of 2026-10-29 · 15 cited facts, 1 with a third-party source · 2 recorded changes · Suggest a correction
At a glance
- Tier
- T3
- Section
- Guardrails & AI security
- Created
- 2024-05-08 repo fix
- Latest release
- last commit 2026-01-12 repo fix
- License
- Apache-2.0 vendor fix
- Pricing
- searched not found fix
- Funding
- Invariant Labs acquired by Snyk (2025-06-24) third-party fix
- Freshness
- 2026-10-29 fix
- Layer
- agent-infra repo fix
- Licensing
- open-source vendor fix
- Protocols
- mcp-client, mcp-server repo fix
- Maintainer health
- 2 issues in 90 days · 0 releases in 12 months · bus factor 1 — as of 2026-11-01 repo
When to use
Optimised for: searched not found
Anti-fit: searched not found
Pros & cons
Pros
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Cons
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Claims & capabilities
As we are entering the agentic era of highly-connected AI systems, relying on multi-turn tool use to achieve complex workflows, the security of these systems has never been more important. This is why today, we are releasing Invariant Guardrails , our state-of-the-art guardrailing system for MCP and agentic AI applications. Guardrails is designed to provide a robust and flexible framework for ensuring the safety and reliability of AI agents, with a focus on contextual guardrailing.
Technical surface
- API surface
- searched not found
- Backend storage
- searched not found
- Deployment
- searched not found
- Embedding model
- searched not found
- Multi-tenancy
- searched not found
- MCP
- searched not found
- A2A
- searched not found
- OpenTelemetry
- searched not found
Similar systems
Other guardrails & ai security in the catalog, ranked by inbound references.
- Azure AI Content Safety Prompt Shields T3
Azure AI Content Safety API that detects user prompt attacks and indirect (document) prompt injection aimed at manipulating a model's behavior, alongside groundedness, protected-material and task-adherence checks.
- Amazon Bedrock Guardrails T3
Configurable safeguards that filter harmful text and image content, redact sensitive information, block denied topics and detect hallucinations. They apply consistently across foundation models in Amazon Bedrock and self-hosted or third-party models.
- Google Cloud Model Armor T3
Runtime security service that screens AI prompts, responses and agent interactions for prompt injection, jailbreaks, malicious URLs, sensitive-data leaks and harmful content, with adjustable confidence thresholds.
- CrowdStrike Falcon Guardian (formerly Pangea AI Guard) T3
AI detection and response product that discovers, governs and secures AI agents at runtime across endpoint, cloud and SaaS. It is built on Pangea, which CrowdStrike agreed to acquire in September 2025, and pangea.cloud's AI Guard page now redirects here.
- Guardrails AI T3
Open-source guardrails framework plus the Guardrails Hub of validators that detect policy violations, hallucinations and data leakage in LLM and agent outputs at runtime. Harvey announced its acquisition of Guardrails AI on Sep 8, 2026.
- Presidio T3
Open-source framework for detecting, redacting, masking and anonymizing PII in text, images and structured data, commonly used to scrub prompts and responses around LLMs. Originally a Microsoft project, it has transitioned to community ownership under Data Privacy Stack.
Sources (14 cited facts, 1 third-party)
Each fact links to the page it came from; the badge says who published it (how to read sources).
- What it is Framework vendor
- What it does & what's distinct Contextual guardrailing layer for agentic and MCP applications that sits at the LLM and … vendor
- Claims / benefits As we are entering the agentic era of highly-connected AI systems, relying on multi-turn… vendor
- Created 2024-05-08 repo
- Latest release last commit 2026-01-12 repo
- License Apache-2.0 vendor
- GitHub https://github.com/invariantlabs-ai/invariant (475★) repo
- Mindshare 475 GitHub stars repo
- Funding Invariant Labs acquired by Snyk (2025-06-24) third-party
- Project & sources https://invariantlabs.ai/blog/guardrails ; https://github.com/invariantlabs-ai/invariant vendor
- licensing-bucket open-source vendor
- taxonomy-three-layer-rollup agent-infra repo
- sdk-languages python registry
- protocol-support mcp-client,mcp-server repo
What changed
Changes to this record's lifecycle, licence, release, pricing and hosting facts, from the catalog's git history. Subscribe (Atom)
Related systems
References (7)
- Anthropic Claude (foundation models) integrates with — Invariant Gateway README has a Anthropic (Messages API) integration section. (verified 2026-10-29)
- AutoGen / AG2 integrates with — Invariant Gateway README has a Microsoft AutoGen integration section. (verified 2026-10-29)
- Google Gemini 3 family integrates with — Invariant Gateway README has a Gemini (generateContent) integration section. (verified 2026-10-29)
- LiteLLM integrates with — Invariant Gateway README has a LiteLLM integration section. (verified 2026-10-29)
- OpenAI GPT family (GPT-5 / GPT-4o / o3 / o4) integrates with — Invariant Gateway README has a OpenAI (Chat Completions/Responses) integration section. (verified 2026-10-29)
- OpenAI Swarm (deprecated) integrates with — Invariant Gateway README has a OpenAI Swarm integration section. (verified 2026-10-29)
- OpenHands integrates with — Invariant Gateway README has a OpenHands integration section. (verified 2026-10-29)