---
title: "aigis vs anything-llm"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/killertcell428-aigis-vs-mintplex-labs-anything-llm"
tools: ["killertcell428-aigis", "mintplex-labs-anything-llm"]
---

# aigis vs anything-llm

*GraphCanon updated Jul 15, 2026*

## Verdict

Pick aigis when aigis is primarily Python; anything-llm is JavaScript; pick anything-llm when anything-llm is primarily JavaScript; aigis is Python.

[aigis](https://pypi.org/project/pyaigis/) reports 51 GitHub stars, 8 forks, and 8 open issues, last pushed Jul 14, 2026. [anything-llm](https://anythingllm.com) has 63k stars, 6.9k forks, and 320 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [aigis's repository](https://github.com/killertcell428/aigis) and [anything-llm's repository](https://github.com/Mintplex-Labs/anything-llm).

| | [aigis](/tools/killertcell428-aigis.md) | [anything-llm](/tools/mintplex-labs-anything-llm.md) |
| --- | --- | --- |
| Tagline | Deterministic, zero-dependency Python firewall for AI agents, MCP rug-pull, memory poisoning, indirect injection, exfil channels. 44 compliance templates (US/CN/JP/EU). | Self-hosted agent experience with deployment scripts for multiple environments |
| Stars | 51 | 63,100 |
| Forks | 8 | 6,907 |
| Open issues | 8 | 320 |
| Language | Python | JavaScript |
| Adopt for | - | Self-hosted AI agent experience with robust deployment scripts across multiple environments. |
| Persona | - | - |
| Runtime | - | - |
| License | Apache-2.0 | MIT |
| Categories | AI Agents, LLM Frameworks, Vector Databases | AI Agents, Inference & Serving |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [aigis](/tools/killertcell428-aigis.md) | [anything-llm](/tools/mintplex-labs-anything-llm.md) |
| --- | --- | --- |
| Days since push | 1d | 0d |
| Open issues (now) | 8 | 320 |
| Owner type | User | Organization |
| Full report | [trust report](/tools/killertcell428-aigis/trust.md) | [trust report](/tools/mintplex-labs-anything-llm/trust.md) |

## Decision facts: anything-llm

- **Adopt for:** Self-hosted AI agent experience with robust deployment scripts across multiple environments.

## Choose when

### Choose aigis if…

- aigis is primarily Python; anything-llm is JavaScript.
- License: aigis is Apache-2.0, anything-llm is MIT.
- Tags unique to aigis: ai-agent, ai-security, compliance, cybersecurity.
- Also covers LLM Frameworks, Vector Databases.
- aigis ships Docker support for self-hosted deployment.

### Choose anything-llm if…

- anything-llm is primarily JavaScript; aigis is Python.
- License: anything-llm is MIT, aigis is Apache-2.0.
- Tags unique to anything-llm: agent-computer, agent-harness, agentic-ai, local-ai.
- Also covers Inference & Serving.
- When you need flexibility in deploying your AI agents on various cloud platforms like AWS, GCP, Digital Ocean, and more.

## When NOT to use aigis

- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

## When NOT to use anything-llm

- Avoid if you require an agent without additional setup or prefer SaaS solutions over self-managed deployments.
- Not suitable for users who are looking for no-code alternatives as setting up AnythingLLM might necessitate some coding knowledge despite offering multiple scripts and methods.

## Common questions

### What is the difference between aigis and anything-llm?

aigis: Deterministic, zero-dependency Python firewall for AI agents, MCP rug-pull, memory poisoning, indirect injection, exfil channels. 44 compliance templates (US/CN/JP/EU).. anything-llm: Self-hosted agent experience with deployment scripts for multiple environments. See the comparison table for live GitHub stats and shared categories.

### When should I choose aigis over anything-llm?

Choose aigis over anything-llm when aigis is primarily Python; anything-llm is JavaScript; License: aigis is Apache-2.0, anything-llm is MIT; Tags unique to aigis: ai-agent, ai-security, compliance, cybersecurity; Also covers LLM Frameworks, Vector Databases; aigis ships Docker support for self-hosted deployment.

### When should I choose anything-llm over aigis?

Choose anything-llm over aigis when anything-llm is primarily JavaScript; aigis is Python; License: anything-llm is MIT, aigis is Apache-2.0; Tags unique to anything-llm: agent-computer, agent-harness, agentic-ai, local-ai; Also covers Inference & Serving; When you need flexibility in deploying your AI agents on various cloud platforms like AWS, GCP, Digital Ocean, and more.

### When should I avoid aigis?

AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

### When should I avoid anything-llm?

Avoid if you require an agent without additional setup or prefer SaaS solutions over self-managed deployments. Not suitable for users who are looking for no-code alternatives as setting up AnythingLLM might necessitate some coding knowledge despite offering multiple scripts and methods.

### Is aigis or anything-llm more popular on GitHub?

anything-llm has more GitHub stars (63,100 vs 51). Stars measure visibility, not whether either tool fits your constraints.

### Are aigis and anything-llm open source?

Yes - both are open-source projects on GitHub (aigis: Apache-2.0, anything-llm: MIT).

### Where can I find alternatives to aigis or anything-llm?

GraphCanon lists graph-backed alternatives at [aigis alternatives](/tools/killertcell428-aigis/alternatives) and [anything-llm alternatives](/tools/mintplex-labs-anything-llm/alternatives) ([aigis markdown twin](/tools/killertcell428-aigis/alternatives.md), [anything-llm markdown twin](/tools/mintplex-labs-anything-llm/alternatives.md)), ranked by typed relationship edges rather than popularity votes.

### Is there a machine-readable version of this comparison?

Yes. The markdown twin at [this comparison](/compare/killertcell428-aigis-vs-mintplex-labs-anything-llm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, aigis or anything-llm?

aigis: Very active. anything-llm: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

### Where are the full trust reports for aigis and anything-llm?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aigis trust report](/tools/killertcell428-aigis/trust); [anything-llm trust report](/tools/mintplex-labs-anything-llm/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=killertcell428-aigis`](/api/graphcanon/graph?tool=killertcell428-aigis)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_
