scpr for AI Automation

scpr: an MCP server for local AI text preprocessing

scpr (Simple Content PRocessor) by AstraBert is an MCP server that provides local text processing for AI agents, designed to sit inside a Model Context Protocol (MCP) workflow. It performs summarization, sentiment analysis, keyword extraction and text cleaning so models receive structured inputs. The package ships as a lightweight, modular Node.js service with explicit MCP integration. Developers and data scientists who run MCP-compatible clients gain reusable preprocessing tools to prepare inputs before model calls.

scpr centralizes common preprocessing and analysis tasks for AI agents

scpr exposes a focused set of text tools that an AI client can call through the MCP interface. The server offers

• Text Summarization to create concise versions of long documents
• Sentiment Analysis to label tone as positive, negative, or neutral
• Keyword Extraction to return salient terms
• Text Cleaning to strip formatting noise

Output fidelity depends on the connected model and input quality

The server produces structured results, but the fidelity of summarization and sentiment labels reflects the underlying AI client's processing model and the language of the source text. scpr is language-agnostic in design, yet the effectiveness of sentiment and summary outputs depends on the model called by the MCP host. Users should validate critical summaries and sentiment calls against original text when accuracy matters.

Installation and integration suit developers familiar with MCP and Node.js

scpr requires an MCP host such as Claude Desktop and a Node.js runtime for installation, and it can be installed via npm or by cloning the repository. Its open-source architecture and modular design make the codebase inspectable and extendable by contributors. The package runs locally within the user environment, and the connected AI client typically performs the heavy inference tasks, so integration work focuses on MCP tool configuration and service linking.

Practical choice for developers who need an MCP-native preprocessing layer

scpr is a practical option for developers and AI practitioners who want a locally hosted, protocol-native way to prepare text before model calls. Expect to manage MCP tool configuration and to verify outputs against source text when correctness is important. Contributing to or customizing the open-source codebase gives teams direct control over processing behavior and adapts the service to specific workflows.