Open Finance MCP
Access your bank data in ChatGPT & Claude via Open Finance
What it does
What if your AI assistant could see your actual bank statements? The Open Finance Data MCP connects your bank account to ChatGPT, Claude, and any MCP-compatible AI — through Brazil's Open Finance. Ask about spending, get summaries, analyze patterns in natural language. No account needed — authenticate via Open Finance (your CPF + your bank). Your data, your control — revoke anytime. Setup takes 2 minutes. Built by Cumbuca, a licensed Payment Institution in Brazil.
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- BABuild AI Trading Agents in Cursor/Claude with an MCP ServerMar 2026 · financialdata.net · ▲6
Connect Your AI to Institutional-Grade Market Intelligence Plug any AI client, from ChatGPT to custom agents, directly into our financial data engine. Get real-time stock prices, fundamentals, institutional trading insights, and other financial data delivered through a universal Model Context Protocol (MCP) server.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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