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onemcp

Verified Safe

by rifkimaulana05

Overview

Connects APIs to AI models using the Model Context Protocol (MCP), generating and caching execution plans for natural-language prompts to ensure accurate, cost-efficient, and high-performance API interaction for AI agents.

Installation

Run Command
docker run -p 8080:8080 admingentoro/gentoro:latest

Environment Variables

  • OPENAI_API_KEY
  • ANTHROPIC_API_KEY
  • GEMINI_API_KEY
  • ARANGODB_PASSWORD
  • GRAPH_INDEXING_ENABLED
  • SERVER_PORT
  • JAVA_OPTS
  • APP_ARGS
  • OTEL_CONFIG
  • OTEL_EXPORTER_OTLP_ENDPOINT
  • BUILD_VERSION

Security Notes

The core Java application utilizes standard libraries for JSON parsing and network requests, avoiding direct 'eval' or dangerous runtime execution from untrusted input. Secrets (like API keys) are configured via environment variables or external configuration, a good practice. However, the default ArangoDB root password of 'test123' in local development scripts and Docker entrypoint presents a significant security risk if not changed in production deployments. The Docker 'entrypoint.sh' allows execution of arbitrary commands passed to the container, which is standard Docker behavior but could be misused in an uncontrolled environment.

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Stats

Interest Score0
Security Score8
Cost ClassMedium
Avg Tokens750
Stars0
Forks0
Last Update2026-01-19

Tags

AI AgentsAPI OrchestrationCachingKnowledge GraphModel Context ProtocolObservabilityLLM Integration