Servidor MCP para CRM con IA
@DavidHolguin
About Servidor MCP para CRM con IA
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Overview
What is Servidor MCP para CRM con IA?
The Servidor MCP para CRM con IA implements the Model Context Protocol (MCP) to provide a secure data processing layer between a CRM and large language models (LLMs). It is designed for developers integrating AI chatbots or lead analysis tools while keeping personal data private.
How to use Servidor MCP para CRM con IA?
Create a .env file with your Supabase credentials, an LLM API key, and a secret key. Install dependencies with pip install -r requirements.txt, then start the server using uvicorn app.main:app --reload. Use the provided REST endpoints for token generation, message sanitization, chatbot context management, Q&A, evaluation, and secure lead analysis.
Key features of Servidor MCP para CRM con IA
- Automatic anonymization of personal data before LLM processing
- Token-based traceability without exposing sensitive information
- Conversational context management for chatbots
- Q&A system with feedback for continuous improvement
- Automated lead potential evaluation and engagement metrics
Use cases of Servidor MCP para CRM con IA
- Secure integration of a CRM with an AI chatbot while protecting customer privacy
- Anonymous lead scoring and tracking based on sanitized interactions
- Continuous quality evaluation of chatbot responses to improve service
- Building a feedback loop for training LLMs without exposing raw PII data
FAQ from Servidor MCP para CRM con IA
How does the server protect personal data?
It automatically anonymizes personal data and replaces it with anonymous tokens before any data reaches the LLM, ensuring sensitive information is never exposed.
What databases does it rely on?
It uses Supabase as its backend, with tables for sanitized messages, conversational context, PII tokens, chatbot contexts, Q&A pairs, and LLM evaluations.
Which LLM providers are supported?
The default configuration uses OpenAI (model GPT-4), but the DEFAULT_LLM_PROVIDER and DEFAULT_LLM_MODEL environment variables allow switching to other providers.
How do I start the server after configuration?
Run uvicorn app.main:app --reload in the project directory after installing the dependencies from requirements.txt.
What endpoints are available for lead analysis?
Use POST /api/v1/analyze-lead to securely analyze a lead and GET /api/v1/lead-metrics/{lead_id} to retrieve historical metrics, both without exposing personal data.
Frequently asked questions
How does the server protect personal data?
It automatically anonymizes personal data and replaces it with anonymous tokens before any data reaches the LLM, ensuring sensitive information is never exposed.
What databases does it rely on?
It uses Supabase as its backend, with tables for sanitized messages, conversational context, PII tokens, chatbot contexts, Q&A pairs, and LLM evaluations.
Which LLM providers are supported?
The default configuration uses OpenAI (model GPT-4), but the `DEFAULT_LLM_PROVIDER` and `DEFAULT_LLM_MODEL` environment variables allow switching to other providers.
How do I start the server after configuration?
Run `uvicorn app.main:app --reload` in the project directory after installing the dependencies from `requirements.txt`.
What endpoints are available for lead analysis?
Use `POST /api/v1/analyze-lead` to securely analyze a lead and `GET /api/v1/lead-metrics/{lead_id}` to retrieve historical metrics, both without exposing personal data.
Basic information
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