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CPFL: Download + OCR

Looks up CPFL information from an official source through one read-only, hosted MCP tool paid with prepaid credits.

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Install CPFL: Download + OCR

Pick your client, then add it in one click or paste the config.

Streamable HTTP (Remote)
Server URL
https://api.mcp.ai/p_contas_cpfl_download_ocr

Remote servers are added in the app, not the config file: Customize → Connectors → Add custom connector, then paste this URL.

Overview

CPFL: Download + OCR is a hosted MCP service for looking up CPFL information from an official source. It exposes one read-only tool through an MCP over HTTP endpoint and uses passwordless magic-link login rather than platform credentials. Use it when an AI client needs this CPFL lookup without deploying or maintaining a local service. Queries are billed from a prepaid credit balance.

Use cases

  • Query CPFL information from an official source
  • Connect an AI agent to the hosted CPFL lookup
  • Ask a compatible MCP client to perform a read-only consultation
  • Use prepaid credits for CPFL queries without managing platform credentials

Key features

  • Official-source CPFL lookup
  • Single read-only MCP tool
  • MCP over HTTP endpoint
  • Passwordless magic-link login
  • Prepaid per-query billing
  • Hosted service with no platform credentials required

Tools7

What CPFL: Download + OCR lets your agent do. Expand a tool for its parameters.

Verified live~1.3k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

6/14 checks healthy over the last 41d

What it can do

From the 7 tools this server returned when we ran it.

Can delete or modify data · 1Handles credentials · 3Makes network requests · 1Read-only tools · 6

Observed 2026-10-16 in an isolated sandbox. A description of reach, not a security audit.

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

Last commit1mo agoMost recent push to the default branch.
Tools exposed7Callable tools this server registers over MCP.

How CPFL: Download + OCR works

What CPFL: Download + OCR does

CPFL: Download + OCR provides an MCP connection to a hosted service for CPFL lookups using an official source. The service is designed for AI clients and agents that need to request this operation through MCP rather than through a separate application interface.

The CPFL: Download + OCR package exposes one operation: contas_cpfl_download_ocr_consultar. The repository describes the operation as an official-source consultation and identifies the server as read-only. It does not provide tools that modify records or data at the source.

How it works

The hosted endpoint is available at https://api.mcp.ai/p_contas_cpfl_download_ocr. An MCP-compatible client sends requests to that URL over MCP over HTTP, and the service handles the hosted lookup. The server does not require credentials for the hosting platform. User access is handled through a passwordless magic link.

Because the service is hosted, the repository functions as a public wrapper containing manifests, documentation, and agent skills; the hosted MCP server itself is proprietary. Requests use a prepaid credit wallet, with each query charged against that balance.

Setup and configuration

Claude Web and Claude Desktop can connect through Claude’s custom connector settings. Cursor and VS Code have installation links in the repository that add the remote HTTP server configuration. Other clients can use the same endpoint if they support MCP over HTTP.

The connection URL is:

text
https://api.mcp.ai/p_contas_cpfl_download_ocr

No environment variables or local service credentials are specified in the provided setup material. Authentication uses the service’s magic-link login flow. For client-specific installation steps, consult the repository’s installation documentation.

Tools and capabilities

The CPFL: Download + OCR server contains one tool:

  • contas_cpfl_download_ocr_consultar: performs the CPFL: Download + OCR consultation against an official source.

The tool is read-only.

Limitations and notes

CPFL: Download + OCR is hosted and proprietary, while the public repository is licensed MIT and contains the wrapper materials. This distinction matters if you need to inspect, deploy, or modify the underlying service.

Usage is not described as free or unlimited: each query consumes prepaid credit. Pricing details are maintained separately in the project documentation.

Data returned by the tool is sent to the LLM host selected by the user, such as Claude, ChatGPT, Cursor, or another agent host. The project identifies that host as a subprocesser outside the service’s control and recommends considering plans with training opt-out options. The tool’s read-only design prevents source changes, but it does not eliminate the data-handling considerations of the selected LLM host.

Read the full README View source on GitHub

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Frequently Asked Questions about CPFL: Download + OCR

CPFL: Download + OCR is an MCP server that connects AI clients to a hosted CPFL official-source lookup service. Its main tool, contas_cpfl_download_ocr_consultar, provides the server’s single read-only operation. Clients connect over MCP over HTTP, authenticate with a passwordless magic link, and pay per query from prepaid credit.

Install it by adding the hosted MCP over HTTP URL to a compatible client: https://api.mcp.ai/p_contas_cpfl_download_ocr. The repository also provides one-click links for Claude, Cursor, and VS Code. Access uses a passwordless magic link rather than platform credentials.

Yes, CPFL: Download + OCR works with Cursor. The repository provides a Cursor installation link that configures the hosted MCP endpoint, and Cursor is listed among the supported clients.

The service uses prepaid credits and charges per query.

Yes, you can use CPFL: Download + OCR with any MCP client that supports MCP over HTTP. Connect that client to https://api.mcp.ai/p_contas_cpfl_download_ocr and complete the service’s magic-link login flow.

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