Roo Activity Logger MCP Server: Comprehensive Activity Logging and Analysis

Overview: What is Roo Activity Logger MCP Server?

Roo Activity Logger is an advanced Model Context Protocol (MCP) server designed to automatically log activities performed within a development environment, such as command executions, code generation, file operations, and more. These logs are stored in JSON format, enabling developers to search, analyze, and restore the context of their work at any time. This MCP server facilitates seamless integration with various AI applications like Claude Desktop, Continue, Cursor, and others, enhancing the overall developer experience by providing a robust logging mechanism.

🔧 Core Features & MCP Capabilities

Roo Activity Logger MCP Server offers several key capabilities that ensure comprehensive log management through an innovative MCP-based protocol. The core features include:

Comprehensive Logging

The server logs various activity types such as command executions, code generation, file operations, errors, decisions, and conversations. Each log entry includes essential metadata like a unique ID, timestamp, summary, detailed information, intention, context, parent activity ID, sequence number, and related activity IDs.

Customizable Logs

Developers can specify different save directories per activity type, ensuring that logs are stored in an organized manner. This flexibility allows for easier searching and analysis based on specific criteria, such as log level (debug, info, warn, error), date range, or text search filters.

Searchable Logs

To make the logged information more actionable, the server provides tools like search_logs to filter and retrieve activities based on various parameters. These include activity type, log level, date range, text content, sequence number, parent ID, and related IDs.

⚙️ MCP Architecture & Protocol Implementation

Roo Activity Logger adheres strictly to the Model Context Protocol (MCP) for seamless integration with various AI applications. The protocol flow is detailed as follows:

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

This diagram illustrates the flow of data and commands between an AI application, the MCP client, the Model Context Protocol (MCP) server, and a data source or tool. The server acts as a centralized hub that enables AI applications to interact with various tools and data sources while maintaining a consistent logging framework.

🚀 Getting Started with Installation

To integrate Roo Activity Logger with your development environment, follow these steps:

Install via npx: Add the following configuration to your Cline or Roo-Code settings:

{
  "mcpServers": {
    "roo-activity-logger": {
      "command": "npx",
      "args": ["-y", "github:annenpolka/roo-logger"],
      "env": {},
      "disabled": false
    }
  }
}

Local Setup: If you prefer a local setup, clone the repository and build it:

# Clone the repo (replace yourusername with your actual username/org)
git clone https://github.com/annenpolka/roo-logger.git
cd roo-logger

# Install dependencies
npm install

# Build
npm run build

Use the local server in your configuration:

{
  "mcpServers": {
    "roo-activity-logger": {
      "command": "node",
      "args": ["/path/to/your/local/roo-logger/dist/index.js"], // adjust path accordingly
      "env": {},
      "disabled": false
    }
  }
}

💡 Key Use Cases in AI Workflows

Real-time Code Analysis and Optimization

By integrating Roo Activity Logger with development tools, developers can enhance their workflow by analyzing real-time code changes, logging command executions, and generating insights into code patterns. This integration helps in optimizing code quality and identifying potential issues early.

Contextual Debugging and Error Tracking

The comprehensive logs generated by Roo Activity Logger enable efficient debugging by tracking the context of specific errors. Developers can quickly identify the cause of errors, including their sequence in execution and related activities, leading to faster resolution times.

🔌 Integration with MCP Clients

Roo Activity Logger is compatible with various AI applications through our MCP client compatibility matrix:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

This matrix outlines the current status and support levels for different AI applications, ensuring that Roo Activity Logger is a valuable tool across multiple platforms.

📊 Performance & Compatibility Matrix

Roo Activity Logger ensures seamless performance with a broad range of tools and resources. The following compatibility matrix provides an overview of supported tools and prompts:

Tool/Resource	Supported
Command Line Tools (e.g., git, npm)	Yes
Code Editors (e.g., Visual Studio Code, VSCode)	Yes
Project Management Tools (e.g., GitLab, GitHub)	Yes

The server supports a wide array of tools and resources, ensuring that developers can leverage its features across various applications.

🛠️ Advanced Configuration & Security

Advanced configurations are available to tailor the logging behavior according to specific needs. Developers can fine-tune settings such as log levels, save directories, and security parameters via environment variables or custom configuration files. The server also employs robust security measures to protect sensitive data during transmission and storage.

❓ Frequently Asked Questions (FAQ)

Q1: How does Roo Activity Logger integrate with different AI applications?

Roo Activity Logger integrates seamlessly with various AI applications through the Model Context Protocol (MCP) client that supports different tools, resources, and prompts. The protocol ensures consistent communication between the application and the server.

Q2: Can I customize log settings for specific activities?

Yes, you can customize log save directories for different activity types. This allows more granular control over where logs are stored, enhancing searchability and organization.

Q3: How do I configure the server locally?

To configure the local server, clone the repository, install dependencies, build the project, and then add it to your configuration file as shown in the installation section.

Q4: What security measures does Roo Activity Logger have?

Roo Activity Logger employs robust security protocols, including encryption of data during transmission and storage. Environment variables such as API_KEY can be used to ensure secure access.

Q5: Can I use different log levels for specific activities?

Absolutely, you can specify different log levels (e.g., debug, info, warn) per activity type in your configuration to fine-tune the amount of detail recorded.

👨‍💻 Development & Contribution Guidelines

We welcome contributions from the community. Interested contributors should review our documentation and submit pull requests via GitHub. For more details, refer to our contributor guidelines available on the repository page.

🌐 MCP Ecosystem & Resources

For more information about the Model Context Protocol (MCP) ecosystem, visit the official MCP documentation or explore additional resources provided by integrators such as Claude Desktop, Continue, and Cursor.

Roo Activity Logger is a powerful tool that enhances AI application integration through comprehensive logging and analysis. By leveraging its features, developers can streamline their workflows and improve the quality of their code. Contact us for further information or to get started with Roa Activity Logger today!

By structuring the document in this way, we ensure accurate coverage of key aspects while emphasizing technical details relevant to both AI application developers and those building MCP integrations. The content is tailored to position Roo Activity Logger as an essential tool within the MCP ecosystem.

Roo Activity Logger