WSB Analyst MCP Server

The WSB Analyst MCP server turns the chaotic, high‑velocity chatter of WallStreetBets into a structured, queryable data set that AI assistants can consume in real time. By leveraging Reddit’s API, the server harvests posts from the r/WallStreetBets subreddit, filters them by score, comment depth, or content type, and then enriches each item with metadata such as author details, timestamps, and embedded links. This curated feed allows developers to ask Claude or any MCP‑compatible LLM questions like “Which stocks are currently receiving the most bullish sentiment on WSB?” or “Show me all external research links shared about AMD.” The server’s ability to surface not only the text but also the context behind it—who posted, how many comments, and what external resources are circulating—provides a richer foundation for market‑analysis prompts.

Key capabilities include real‑time progress reporting during data collection, ensuring that AI clients receive incremental updates rather than waiting for a bulk download. The server also ships with ready‑to‑use analysis templates that embed domain‑specific prompts, enabling developers to jump straight into market‑analysis workflows without crafting long custom prompts. By exposing these tools through the MCP interface, the server integrates seamlessly with Claude Desktop’s hammer‑icon tool palette and can be invoked via slash commands, making it a first‑class citizen in the assistant’s toolset.

For developers building finance or trading applications, this MCP server offers several compelling use cases. A portfolio manager could query the latest WSB sentiment to surface potential short‑selling opportunities, while a research analyst might harvest external links shared by the community to discover emerging market narratives. Because the server aggregates data on demand, it can support dynamic dashboards that refresh with each user query, eliminating the lag inherent in static data feeds. The integration also works with any MCP client, not just Claude, allowing teams to plug the service into custom workflows or internal tooling.

What sets WSB Analyst apart is its combination of real‑time data ingestion, granular filtering, and AI‑ready templating. Rather than treating Reddit posts as raw text, the server transforms them into a structured knowledge base that LLMs can interrogate efficiently. Developers benefit from reduced boilerplate: the MCP server handles authentication, pagination, and data enrichment, while the client focuses on prompt design and user interaction. In short, WSB Analyst turns a noisy social‑media channel into actionable intelligence for AI‑driven financial analysis.