MCP Servers

Run:AI MCP Server

Enables LLM agents to control NVIDIA Run:AI infrastructure by dynamically searching and executing over 426 Run:AI APIs through MCP tools.

README

Run:AI MCP Server

NVIDIA Run:AI 인프라를 LLM 에이전트가 제어하는 MCP(Model Context Protocol) 서버.

426개 Run:AI API를 4개 메타 도구 + BM25 검색 엔진으로 동적 검색·실행합니다.

도구

도구	설명
`search_runai_api_spec`	OpenAPI 스펙 BM25 검색 — 엔드포인트, 메서드, 스키마 반환
`call_runai_api`	REST API 호출 (인증 자동, DELETE 시 confirm 필요)
`resolve_runai_names`	엔티티 이름 → ID 변환 (cluster, project, workload 등)
`execute_runai_cli`	CLI 전용 작업 (port-forward, exec, logs, attach, diagnostics)

워크플로우

search_runai_api_spec("create training workload")
  → resolve_runai_names([{ type: "project", name: "my-project" }])
  → call_runai_api({ method: "POST", path: "/api/v1/workloads/trainings", ... })

설치

npm install
npm run build

인증

Run:AI UI에서 Application (서비스 계정) 생성 → clientID + clientSecret 발급. 서버가 자동으로 POST /api/v1/token (client_credentials grant)으로 JWT를 발급·갱신합니다.

cp .env.example .env
# RUNAI_CLIENT_ID, RUNAI_CLIENT_SECRET 설정

정적 토큰(RUNAI_API_TOKEN)도 지원하나, JWT는 만료되므로 서비스 계정 방식을 권장합니다.

Claude Code MCP 설정

~/.claude/mcp.json:

{
  "mcpServers": {
    "runai": {
      "command": "node",
      "args": ["/path/to/runai-mcp-server/dist/index.js"],
      "env": {
        "RUNAI_API_BASE_URL": "https://your-instance.run.ai",
        "RUNAI_CLIENT_ID": "your-client-id",
        "RUNAI_CLIENT_SECRET": "your-client-secret"
      }
    }
  }
}

개발

npm run dev      # ts-node 개발 실행
npm test         # 전체 테스트
npm run build    # 프로덕션 빌드

아키텍처

Registry Builder: OpenAPI 3.0.3 스펙을 파싱하여 413개 OperationDescriptor 생성, $ref 자동 해결
BM25 Search: IDF 기반 키워드 검색 + 동의어 확장 (job→workload, remove→delete 등)
Adaptive Schema: 검색 결과 1-2개면 requestBody 스키마 포함, 3개+면 summary만 (토큰 절약)
Safety: DELETE는 confirm_destructive 필수, CLI는 화이트리스트 + 쉘 인젝션 방어

라이선스

MIT

Recommended Servers

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official

Featured

TypeScript

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official

Featured

Local

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official

Featured

TypeScript

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official

Featured

Python

E2B

Using MCP to run code via e2b.

Official

Featured

Neon Database

MCP server for interacting with Neon Management API and databases

Official

Featured

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official

Featured

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official

Featured