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MCP Server: Trend Data Persister

by Flow-Research

This project implements an MCP server using Python to persist trend data (upward or downward) into a PostgreSQL database. It exposes a single tool, `persist-trend-data`, which accepts a database connection string and JSON data representing the trend.

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What is MCP Server: Trend Data Persister?

This MCP server provides a tool to persist trend data (upward or downward) into a PostgreSQL database. It uses Pydantic for input validation and psycopg2 to interact with the database.

How to use MCP Server: Trend Data Persister?

  1. Clone the repository. 2. Configure your MCP client to connect to the server, providing the path to the Makefile. 3. Send requests to the persist-trend-data tool with a datasource_url and json_data containing the trend information.

Key features of MCP Server: Trend Data Persister

  • Persists upward and downward trends

  • Uses PostgreSQL as a data store

  • Validates input data with Pydantic

  • Provides a Makefile for easy setup and running

  • Integrates with MCP clients

Use cases of MCP Server: Trend Data Persister

  • Tracking positive performance trends (e.g., rockstars)

  • Identifying negative performance trends (e.g., culprits)

  • Storing trend data for analysis and reporting

  • Integrating trend data into MCP-based workflows

  • Automating data persistence for trend analysis

FAQ from MCP Server: Trend Data Persister

What database does this server support?

This server is designed to work with PostgreSQL.

What are the prerequisites for running this server?

You need Python (>=3.10 recommended), make, uv (optional), and access to a running PostgreSQL database.

How do I configure my MCP client to use this server?

Configure your MCP client to connect to this server. The cwd path should point to the correct project directory where the Makefile resides.

What kind of data does the server expect?

The server expects JSON data with a 'trend' field (either 'upward' or 'downward') and corresponding arrays of 'rockstars' or 'culprits', each with 'name', 'department', and 'amount' fields.

How do I run the server?

You can run the server using the make run command in the project directory.