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"Adding functionality to large language models" matching MCP servers:

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    agentcentral is a hosted MCP server for Amazon sellers that connects Claude, ChatGPT, and other AI clients to Amazon Ads, Seller Central, inventory, orders, catalog, rankings, finance, and fulfillment data. It provides fast reads from pre-materialized Amazon data, scoped API keys, OAuth-based Amazon connections, encrypted tokens, per-tenant isolation, and guarded write tools with audit log
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    MIT
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    A Model Context Protocol server that provides real-time global currency exchange rate queries, enabling large language models to access up-to-date currency exchange information.
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    MCP server for tracking personal expenses using FastMCP and SQLite, enabling adding, listing, updating, deleting expenses and summarizing by category via natural language tools.
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    Connects AI agents to the Base network for onchain data, batch USDC payments, and access to over 200 AI models. It utilizes the x402 protocol to enable pay-per-request functionality using USDC without requiring traditional API keys or accounts.
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    MIT
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    Provides an MCP server that allows large language models to access real-time and historical Bitcoin market data from Binance, including current prices, order book data, recent trades, and price history through a standardized interface.
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    MIT
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    The MCP provides comprehensive financial data and analytical tool support for AI large language models, specifically including the following five core data capabilities: Stock Analysis/ETF Analysis/Public Funds/News & Information/General Tools More Info: https://github.com/shenqingtech/deepq-finan
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    ISC
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    Enables AI assistants to interact with EzBookkeeping for personal finance management through natural language, including adding transactions, checking balances, and generating reports.
    MIT
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    Provides AI models with secure access to Interactive Brokers trading data and functionality, enabling account management, market data retrieval, and trading operations through natural language interactions.
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    MIT
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    Enables Large Language Models to access and query Tally Prime ERP data, including financial reports, masters, and inventory summaries, via the Model Context Protocol.
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    MIT
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    A Python implementation that enables Large Language Models to interact with PayPal's APIs through function calling, supporting features like invoices, orders, products, subscriptions, and transactions.
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    MIT
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    Provides AI assistants with direct access to HLedger accounting data and functionality, enabling natural language queries for balances, reports, journal entries, and financial analysis.
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    MIT
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    Provides real-time financial data from Yahoo Finance to Large Language Models through the Model Context Protocol, enabling AI models to access stock prices, historical data, and company information.
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    MIT
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    A server that implements the Model Context Protocol for Schwab API, allowing access to account information, positions, stock quotes, and order/transaction history designed for integration with Large Language Models.
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    MIT
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    Enables natural language expense tracking and management via Claude Desktop, supporting adding, listing, summarizing, updating, and deleting expenses with flexible date parsing and category filtering.
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    Enables personal finance tracking through Claude Desktop using natural language to manage income and expenses with persistent SQLite storage. Supports adding and deleting transactions, checking balances, and viewing spending summaries grouped by category or month.
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    A server application that enables large language models to execute stock trading operations through QMT trading system, providing functionality for account queries, position management, and order placement.
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    An MCP server that provides Large Language Models with access to YNAB (You Need A Budget) budgets, allowing them to fetch budget data including accounts, categories, and category groups.
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    Enables management of expenses via SQLite database, including adding, listing, updating, deleting, filtering, and summing expenses through natural language.