near-ai-cloud
NEAR AI Cloud private inference and verification
Install / Use
npx skills add internet-court/internet-court-skill --skill near-ai-cloudInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of near-ai-cloud
near-ai-cloud scores 83/100 on our quality scale, 1239th of 2,569 Development & Engineering skills we index (top 49%).
Its SKILL.md is 4.9 KB long, well organised into 8 sections with 3 code examples: a solid amount of guidance for an agent.
With 6,129 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 38 days ago, so near-ai-cloud is actively maintained.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
near-ai-cloud compared with similar skills
All 4 of these similar skills score higher than near-ai-cloud; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| near-ai-cloud (this skill)by internet-court | 83 | 6.1k | 38d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.6k | 11d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 73.9k | today | CLAUDE.md |
| ai-job-searchby MadsLorentzen | 100 | 44.0k | 6d ago | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | today | CLAUDE.md |
Frequently asked questions
- How do I install near-ai-cloud?
- Run
npx skills add internet-court/internet-court-skill --skill near-ai-cloud. The install tabs above show the steps for each supported agent. - Which AI agents does near-ai-cloud work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is near-ai-cloud safe to use?
- It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is near-ai-cloud still maintained?
- The repository was last updated 38 days ago, so near-ai-cloud is actively maintained.
Skill content
View source on GitHubname: near-ai-cloud description: NEAR AI Cloud private inference and verification. Use when integrating NEAR AI Cloud API for verifiable private AI inference, verifying model or gateway TEE attestation (NVIDIA NRAS, Intel TDX), verifying chat message signatures, implementing end-to-end encrypted chat, or using the OpenAI-compatible API with NEAR AI Cloud. metadata: author: near version: "1.0.0"
NEAR AI Cloud
Verifiable private AI inference through Trusted Execution Environments (TEEs). All inference runs inside Intel TDX confidential VMs with NVIDIA TEE GPUs — your data stays encrypted and isolated from infrastructure providers, model providers, and NEAR itself.
Quick Start
The API is OpenAI-compatible. Point any OpenAI SDK at https://cloud-api.near.ai/v1:
import openai
client = openai.OpenAI(
base_url="https://cloud-api.near.ai/v1",
api_key="YOUR_API_KEY" # from cloud.near.ai dashboard
)
response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-V3.1",
messages=[{"role": "user", "content": "Hello, NEAR AI!"}]
)
print(response.choices[0].message.content)
import OpenAI from 'openai';
const openai = new OpenAI({
baseURL: 'https://cloud-api.near.ai/v1',
apiKey: 'YOUR_API_KEY',
});
const completion = await openai.chat.completions.create({
model: 'deepseek-ai/DeepSeek-V3.1',
messages: [{ role: 'user', content: 'Hello, NEAR AI!' }]
});
console.log(completion.choices[0].message.content);
How It Works
- All inference runs inside Intel TDX confidential VMs with NVIDIA TEE GPUs
- TLS terminates inside the TEE, not at a load balancer — prompts are never exposed in plaintext
- TEEs generate cryptographic attestation proofs verifiable via NVIDIA NRAS and Intel TDX
- Every chat response is signed by a key that never leaves the TEE
- You can independently verify hardware attestation and bind it to message signatures
Verification Flow
1. Generate nonce
2. Request model attestation → get signing_address, nvidia_payload, intel_quote
3. Verify GPU attestation → submit nvidia_payload to NVIDIA NRAS, check JWT fields
4. Verify CPU attestation → verify intel_quote via dcap-qvl or TEE Explorer
5. Verify GPU-CPU binding → signing_address + nonce bound in TDX report data; same nonce in NRAS eat_nonce
6. Make chat request → use the API as normal
7. Fetch chat signature → GET /v1/signature/{chat_id}
8. Verify signature → recover signer, compare to attested signing_address
API Endpoints
Base URL: https://cloud-api.near.ai
| Endpoint | Method | Description |
|----------------------------------------|--------|------------------------------------|
| /v1/chat/completions | POST | OpenAI-compatible chat completions |
| /v1/models | GET | List available models |
| /v1/attestation/report?model={model} | GET | Model attestation (GPU + CPU) |
| /v1/attestation/report | GET | Gateway attestation |
| /v1/signature/{chat_id} | GET | Chat message signature |
Critical Knowledge
- Base URL is
https://cloud-api.near.ai/v1— use with any OpenAI SDK signing_algocan beecdsaored25519- Nonce should be a random 64-char hex string (32 bytes) for attestation freshness
- NRAS response is a two-part array:
[["JWT", "..."], {"GPU-0": "..."}]— overall JWT + per-GPU JWTs - The
signing_addressfrom model attestation must match the address that signed chat messages - Chat signatures are persistent and can be queried at any time after completion
References
| Topic | File | |----------------------------------|----------------------------------------------------------------------| | Private vs Anonymised Models | references/private-vs-anonymised.md | | Model TEE verification | references/model-verification.md |
Planned:
- Gateway verification (TDX attestation for the API gateway + source provenance)
- Chat verification (request/response hashing + signature verification)
- E2E encrypted chat (ECDH key exchange, AES-256-GCM / ChaCha20-Poly1305)
- OpenAI compatibility (streaming, reasoning models, Files API)
Resources
- NEAR AI Cloud: https://cloud.near.ai
- Documentation: https://docs.near.ai/cloud/introduction
- Verification Example: https://github.com/near-examples/nearai-cloud-verification-example
- Full Verifier: https://github.com/nearai/nearai-cloud-verifier
- NVIDIA NRAS API: https://docs.api.nvidia.com/attestation/reference/attestmultigpu_1
- TEE Attestation Explorer: https://proof.t16z.com/
- DCAP QVL (TDX verification): https://github.com/Phala-Network/dcap-qvl
Related Skills
Agent-Reach
85.6kGive your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
headroom
73.9kCompress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
ai-job-search
44.0kThe job search that runs on your machine. AI job application framework built on Claude Code: evaluate postings, tailor CVs, write cover letters, prep interviews. Fork it and own it.
claude-howto
41.7kA visual, example-driven guide to Claude Code — from basic concepts to advanced agents, with copy-paste templates that bring immediate value.
Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
