Prometeo MCP Server

Prometeo MCP Server is a lightweight, Python‑based implementation of the Model Context Protocol (MCP) that exposes the full functionality of the Prometeo API to AI assistants. By running as an MCP server, it turns Prometeo’s banking and identity‑verification services into first‑class tools that can be invoked directly from LLM agents, plugins or any other MCP‑compatible workflow. The server bridges the gap between a conversational AI and real‑world financial data, enabling developers to build smarter, context‑aware applications without handling API keys or authentication logic in the assistant itself.

The server solves a common pain point for developers: integrating external data sources into an LLM’s toolset while keeping credentials secure and operations idempotent. With a single command, the MCP server can be launched inside environments such as Claude Desktop, OpenAI GPTs, LangChain or OpenInterpreter. Once running, the server registers a set of tools—CURP queries and bank account validation—that can be called by name from the assistant. The assistant merely passes parameters; the server authenticates with Prometeo, performs the request, and returns a structured response. This pattern keeps sensitive keys out of the assistant’s memory and allows the server to manage retries, rate‑limits and caching centrally.

Key capabilities are presented in plain language:

• CURP Query – Validate a Mexican unique identity code or reverse‑lookup the CURP from demographic data.
• Account Validation – Verify bank account details across multiple Latin American countries and the U.S., supporting formats such as CLABE, CBU/CVU, PIX keys, and more.
• Asynchronous Result Retrieval – Fetch the status of a previously initiated validation, useful for long‑running checks.

These tools are packaged as MCP resources with clear schemas defined by Pydantic v2, ensuring type safety and consistent error handling for the AI client. The server’s integration with FastMCP guarantees low latency, while the Prometeo SDK handles authentication and request orchestration.

Typical use cases include:

• Financial onboarding – An assistant can confirm a user’s bank account before initiating a transfer.
• Identity verification – A chatbot can validate a CURP during account creation or fraud prevention checks.
• Regulatory compliance – Automated workflows can audit banking details against national formats in real time.
• Data enrichment – Enrich user profiles with verified personal data without exposing raw API calls.

By abstracting the Prometeo API behind MCP, developers gain a secure, scalable bridge that can be embedded in any LLM‑driven system. The server’s minimal dependencies (Python 3.11+, Pydantic, FastMCP) and straightforward launch commands make it a plug‑and‑play solution for building AI applications that need reliable access to banking and identity data.