Context-Engine

🥈Silver

Context-Engine MCP compresses and manages context for AI agents, improving efficiency and accuracy in operations. It benefits teams using AI agents for tasks like code generation, data analysis, and customer support. The tool connects to various AI models and databases, streamlining workflows and reducing latency.

373340Updated 1w ago

Intermediate30min to implementautomation

Saves ~180 min per use

Quick InstallView Source

git clone https://github.com/Context-Engine-AI/Context-Engine.git

Works with:

Claude

Overview

About This Skill

How to Use

["Identify the task or workflow where Context-Engine MCP can optimize context. For example, if you're using an AI agent for code generation, specify the repository, dependencies, and recent changes that need to be considered.","Gather the relevant data sources (e.g., databases, APIs, or documents) that the AI agent needs to access. Use Context-Engine MCP to connect to these sources and extract the most pertinent information.","Define the key objectives or constraints for the task. For instance, if the task is data analysis, specify whether the focus is on trends, anomalies, or specific metrics.","Run Context-Engine MCP to compress and structure the context. Review the optimized context summary to ensure it captures all critical details without unnecessary noise.","Provide the optimized context to the AI agent and monitor its performance. Adjust the context sources or objectives if the agent requires additional or refined information."]

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/Context-Engine-AI/Context-Engine

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Use Context-Engine MCP to optimize the context for an AI agent handling [TASK_DESCRIPTION]. Focus on [KEY_OBJECTIVES], such as [OBJECTIVE_1], [OBJECTIVE_2], or [OBJECTIVE_3]. Ensure the agent has access to the most relevant data from [DATABASE/SOURCE_1], [DATABASE/SOURCE_2], or [DATABASE/SOURCE_3] while minimizing noise. Provide a structured summary of the optimized context for the agent to use.

Example Output

For a customer support AI agent tasked with resolving a billing dispute, Context-Engine MCP optimized the context by extracting and compressing the following key data points from the CRM and billing system:

1. **Customer Profile**: Jane Doe (Customer ID: CUST-45678), active since 2022, premium subscription tier, and a history of 3 prior billing disputes resolved in her favor.

2. **Current Issue**: Duplicate charge of $49.99 on invoice #INV-2024-0589, dated May 15, 2024. The charge appears for the "Premium Support Add-on" service, which Jane claims she never subscribed to.

3. **Support Interaction History**: Jane contacted support on May 16 via chat, where the agent escalated the issue to the billing team but no resolution was provided. The chat transcript indicates Jane was frustrated and requested a callback.

4. **Billing System Data**: The duplicate charge is linked to a system glitch in the subscription management module, which erroneously added the "Premium Support Add-on" to Jane’s account on May 14. The glitch has since been patched, but the charge remains.

5. **Policy Context**: According to company policy, duplicate charges for services not explicitly subscribed to should be refunded within 24 hours of verification. Jane’s account qualifies for this policy.

**Optimized Context Summary**:
- **Primary Issue**: Duplicate charge for unsubscribed service.
- **Customer Sentiment**: Frustrated, escalated to billing team.
- **Resolution Path**: Refund the $49.99 charge immediately and credit Jane’s account with a 10% discount on her next bill for the inconvenience.
- **Next Steps**: Notify Jane via email with the refund confirmation and discount code, and log the issue in the system to prevent recurrence.

The AI agent now has a concise, actionable context to resolve the issue efficiently without sifting through irrelevant data.