BankMCP

Cata-centavo is a self-hosted MCP server that gives compatible AI agents read-only access to a user's Brazilian Open Finance bank, credit-card, and investment accounts through Pluggy. It runs locally over stdio, reads existing Pluggy connections identified by environment variables, and supports queries about transactions, spending categories, account balances, current card statements, unfamiliar charges, and investments. It has no hosted or multi-user service. The package runs with Node.js 22.13 or newer and can be launched with npx. Its main commands include the MCP server itself, `init` for checking credentials and configured connections, and `doctor` for diagnosing connection status, consent, local cache, and learned categorization data. Provider transaction categories are copied into a persistent local `data.db`; the server also learns merchant-category associations from the user's transactions, and manually corrected or newly assigned categories are retained locally and applied retroactively.

Enable Banking is an open-banking infrastructure platform that provides a single PSD2-compliant API for connecting products to more than 2,700 banks across 30 European countries. It supports real-time account information and payment initiation for business and personal accounts, while handling bank-specific APIs, authentication methods, API updates, and regulatory changes. The platform provides documentation, sandbox environments, and engineering support.

Desktop Commander MCP is an open-source Model Context Protocol server that lets AI assistants search, read, write, move, and edit files; run terminal commands and code; and manage interactive or long-running processes. It is built on the MCP Filesystem Server and adds search-and-replace editing, streamed command output, session management, process controls, configurable timeouts, and background execution. It also supports file previews and Markdown editing, data analysis for CSV, JSON, and Excel files, and native operations on Excel, PDF, and DOCX documents. The repository documents use with Claude Desktop and other MCP clients, as well as remote AI control through ChatGPT, Claude web, and other AI services. Its associated Desktop Commander App adds a graphical interface, live file-change previews, arbitrary model support, and custom MCP configuration.

Model Context Protocol (MCP) is an open, standardized protocol layer for connecting large language models and AI agents with external data sources, hosted infrastructure tools, and other contextual data. It defines formats, metadata, protocol schemas, and APIs for sharing information and tools, attaching, referencing, and validating context such as documents, embeddings, and provenance, while supporting scoped authentication and permissions. MCP translates JSON requests from an agent into calls to service APIs, including CRM, container-management, and GKE capabilities, and can provide design-system context and related tools for generating consistent applications. The official project publishes its specification, documentation, and protocol schema; the schema is defined first in TypeScript and also provided as JSON Schema for broader compatibility. The protocol was created by David Soria Parra and Justin Spahr-Summers, is hosted at modelcontextprotocol.io, and is licensed under the MIT License.

Awesome MCP Servers is a curated collection of Model Context Protocol (MCP) server implementations, maintained as a GitHub repository with a synchronized web directory. It catalogs production-ready and experimental servers that let AI models interact with local and remote resources through standardized interfaces, including file access, databases, API integrations, browser automation, cloud platforms, research services, and other contextual tools. The repository organizes entries by capability, programming language, deployment scope, operating system, and whether an implementation is official.