Sales MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Sales MCP ServerShow 2025 enterprise sales and investigate anomalies."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
LangGraph MCP Prefab UI Demo
This is the companion repository for the blog post TODO: add Medium link.
The goal of this demo is to show a LangGraph skills agent inside an MCP client with an inline Prefab UI. The example uses a sales analytics skill, a local SQLite database, and human-in-the-loop review buttons.
Prerequisites
Python 3.11+
Make,
curl, andtarAn OpenAI API key, unless you configure the demo to use Ollama
An MCP client that can launch a stdio server and render MCP Apps UI
Setup
Install the Python dependencies:
make installCreate your local environment file:
cp .env.example .envEdit .env and set:
OPENAI_API_KEY=sk-...Seed the demo database:
make seedRun
Start the sales MCP server:
make sales-mcpIn a second terminal, start the LangGraph skills agent:
make skills-agentKeep both terminals running while you use the demo.
MCP Client
Add this server command to your MCP client config:
uv --directory /ABSOLUTE/PATH/TO/langgraph-mcp-prefab-ui run python -m langgraph_prefab_ui.prefab_serverUse these environment variables for that MCP server:
LANGGRAPH_URL=http://127.0.0.1:2024
LANGGRAPH_ASSISTANT_ID=skills_agentReplace /ABSOLUTE/PATH/TO/langgraph-mcp-prefab-ui with the path to your clone.
Then ask your MCP client:
Show 2025 enterprise sales and investigate anomalies.You should see an inline dashboard with the sales trend, source rows, and Investigate / Dismiss buttons.
Notes
Start
make sales-mcpbeforemake skills-agent.The first
make skills-agentrun downloads the pinned skills-agent release into.skills-agent/.
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