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elasticsearch_mcp_n8n_telegram_bot

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by Som23Git

Overview

AI-powered conversational expense tracking and querying via Telegram, leveraging AWS Bedrock LLMs and Elasticsearch's Agent Builder for ingestion and retrieval.

Installation

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Environment Variables

  • TELEGRAM_BOT_TOKEN
  • SARVAM_ENDPOINT
  • SARVAM_API_KEY
  • AWS_ACCESS_KEY_ID
  • AWS_SECRET_ACCESS_KEY
  • AWS_REGION
  • ELASTICSEARCH_API_KEY
  • ELASTICSEARCH_CLOUD_URL
  • ELASTICSEARCH_INDEX_NAME

Security Notes

The system relies on n8n's credential management for sensitive API keys (Telegram, AWS, Elasticsearch, Sarvam STT), which is a good practice. LLM outputs are explicitly parsed for JSON objects with custom code, avoiding dangerous functions like `eval`. A hardcoded user ID is used for access control, which is basic but effective for a personal bot. The `_example.json` shows placeholders, emphasizing the need for secure configuration over hardcoding. General LLM hallucination is acknowledged as a risk.

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Stats

Interest Score0
Security Score7
Cost ClassMedium
Avg Tokens500
Stars0
Forks0
Last Update2025-11-28

Tags

Conversational AIExpense TrackingTelegram BotElasticsearchLLM Orchestration