Build a Slack AI Agent with LangGraph + MCP | Full Setup

Learn how to build a Slack AI Agent with LangGraph and MCP in this full setup tutorial. Dive into #AIagents and #GPT4 technology for your own #FinancialAI projects.
In this video, I walk you through how to build a Slack-based financial analyst agent using LangGraph + MCP (Model Context Protocol) — perfect for AI engineers and builders exploring how to create tool-using agents that can summarize earnings reports, pull SEC filings, and respond in Slack using markdown formatting.

You’ll learn how to:

- Set up an MCP server with financial tools (like get_stock_summary, get_sec_filings, get_analyst_targets)
- Connect the server to a LangGraph agent with create_react_agent
- Run the agent with a Slack interface for real-time interaction
- Use MCP Inspector to test your tools

See the full code in the repo

???? GitHub Code Repo:
https://github.com/hollaugo/tutorials/tree/main/mcp-financial

???? Example Prompts to Try:

“Give me a summary of Apple and its latest earnings.”

“What are the analyst recommendations for Nvidia?”

“Summarize Tesla’s most recent 10-Q.”

⚡ Tech Stack:

- LangGraph
- FastMCP
- Slack Bolt (Python)
- FastAPI
- yFinance + SEC Edgar Fillings
- OpenAI GPT-4

???? If you want help building or deploying LangGraph-based agents for internal tools, client projects, or financial workflows — reach out or drop your questions in the comments