MCP Order Flow Server

The MCP Order Flow Server is a purpose‑built, high‑performance platform that delivers real‑time order flow analytics to algorithmic trading systems. By bridging market data brokers via gRPC, it translates raw feed streams into actionable microstructure insights—such as absorption, stacking, and sweep patterns—that are typically only available to institutional traders. For developers building AI‑powered trading assistants, this means a single, protocol‑compliant endpoint that can be queried by LLMs to surface nuanced market behavior without the need for custom data ingestion pipelines.

At its core, the server exposes a single MCP tool, , which accepts a ticker symbol and a historical window. The response is an XML payload containing comprehensive metrics: bid‑ask dynamics, size acceleration, momentum indicators, and algorithmically derived support/resistance levels. Because the server adheres strictly to MCP standards, any AI agent that understands the protocol can invoke this tool, parse the response, and incorporate the insights directly into strategy generation or risk management workflows. This tight coupling eliminates latency pitfalls; gRPC’s sub‑millisecond round trips ensure that the analytics are as fresh as the underlying feed.

Key capabilities include:

• Real‑time microstructure processing that aggregates thousands of quotes per second.
• Pattern detection for absorption, stacking, and sweeps, flagging potential institutional intent.
• Momentum metrics that quantify bid/ask movements and size shifts over short windows.
• Support/resistance extraction, providing algorithmic levels that can be fed into trading rules.
• MCP compliance, enabling seamless integration with Claude, GPT‑4o, or any LLM that supports the protocol.

Typical use cases span algorithmic execution platforms seeking to improve trade timing, portfolio managers wanting to surface hidden liquidity signals, and research teams building predictive models on microstructure features. In a production environment, an AI assistant could call the tool whenever a new trade signal is generated, instantly receive a distilled snapshot of market intent, and decide whether to trigger an order or wait for confirmation.

What sets this server apart is its combination of institutional‑grade analytics with an open, protocol‑first interface. Developers can embed sophisticated order flow reasoning into conversational agents or autonomous trading bots without wrestling with low‑level feed parsing, allowing them to focus on strategy logic and risk controls while the MCP server handles data fidelity and performance.