onyx-model-server

A model server for running and serving machine learning models, particularly focused on LLM inference with support for various model formats and optimization techniques

Evaluated Mar 17, 2026 (0d ago)
Homepage ↗ Repo ↗ AI & Machine Learning model-serving inference machine-learning llm gpu deep-learning
⚙ Agent Friendliness
22
/ 100
Can an agent use this?
🔒 Security
18
/ 100
Is it safe for agents?
⚡ Reliability
25
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
0
Documentation
30
Error Messages
0
Auth Simplicity
100
Rate Limits
0

🔒 Security

TLS Enforcement
0
Auth Strength
0
Scope Granularity
0
Dep. Hygiene
50
Secret Handling
50

No authentication or TLS enforcement documented. Appears designed for trusted internal networks. No security hardening guidance provided.

⚡ Reliability

Uptime/SLA
0
Version Stability
30
Breaking Changes
50
Error Recovery
20
AF Security Reliability

Best When

You need high-performance model inference with GPU acceleration and support for multiple model formats

Avoid When

You only need simple model serving without optimization requirements or are working with non-neural network models

Use Cases

  • Serving large language models for inference
  • Running ML models in production environments
  • Building AI-powered applications with model serving backend
  • Deploying transformer models at scale
  • Creating custom model inference endpoints

Not For

  • Model training or fine-tuning
  • Small-scale prototyping without GPU resources
  • Non-ML computational workloads
  • Data preprocessing pipelines

Interface

REST API
Yes
GraphQL
No
gRPC
No
MCP Server
No
SDK
No
Webhooks
No

Authentication

OAuth: No Scopes: No

No authentication mechanisms documented - appears to be designed for internal/trusted network deployment

Pricing

Model: open-source
Free tier: Yes
Requires CC: No

Open source software - costs are infrastructure-based (GPU/compute resources)

Agent Metadata

Idempotent
Unknown
Retry Guidance
Not documented

Known Gotchas

  • No documented API authentication
  • Minimal API documentation
  • No rate limiting information
  • No structured error responses documented

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Scores are editorial opinions as of 2026-03-17.

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