Devtap
devtap is a tool that automatically bridges the output of build/development commands to AI programming sessions. It captures stdout/stderr and provides it to AI programming assistants via the MCP protocol, supporting multi-agent parallel sessions and cross-machine build scenarios.
rating : 2.5 points
downloads : 5.7K
What is devtap?
devtap is a development efficiency tool designed to address the pain point of manually copying and pasting build error logs during the development process. It automatically captures the output when you run build commands (such as cargo check, npm run build, etc.) and pushes this information in real-time to your AI programming assistant (such as Claude Code, Codex CLI, etc.), allowing the AI to immediately see build errors and help you fix them.How to use devtap?
Using devtap is very simple: 1) Install the devtap tool; 2) Configure the integration with your AI programming assistant; 3) Run your build commands with devtap; 4) The AI assistant will automatically obtain the build output and help you fix the problems. There is no need to manually copy and paste any logs throughout the process.Applicable scenarios
devtap is particularly suitable for the following scenarios: 1) Multi-process local development (front-end + back-end + worker processes); 2) Multiple AI assistants collaborating on the same project; 3) Build output from remote machines (CI/CD, development servers) needs to be fed back to the local AI assistant; 4) Any development workflow that requires automatically passing build/test output to an AI assistant.Main features
Automatically capture build output
Automatically capture the stdout and stderr output of any command, including build errors, test failures, compilation warnings, etc., without manual intervention.
MCP protocol integration
Seamlessly integrate with mainstream AI programming assistants (Claude Code, Codex CLI, OpenCode, etc.) via the Model Context Protocol to enable two-way communication.
Support for multiple AI assistants
Support sending the same build output to multiple AI assistants simultaneously, with each assistant consuming its own copy independently without interference.
Cross-machine workflow
Support automatic feedback of remote build (such as CI server) output to the local AI assistant, enabling a true distributed development feedback loop.
Automatic retry loop
When integrated with Claude Code, an automatic retry mechanism can be configured to prevent the AI assistant from stopping when there are build errors until the problem is resolved.
Flexible storage backend
Support file storage (default) and GreptimeDB database storage. The latter provides SQL query, historical record, and cross-machine synchronization functions.
Advantages
Significantly improve development efficiency: No need to manually copy and paste build error logs.
Real-time feedback: Build errors are immediately pushed to the AI assistant, shortening the feedback loop.
Support multiple tools: Well integrated with mainstream AI programming assistants.
Flexible deployment: Support local and cross-machine workflows.
Data security: All data is stored locally and not sent to external servers.
Open source and free: Licensed under the MIT license and completely free to use.
Limitations
Requires configuration: Installation and integration configuration are required for the first use.
Depends on the MCP protocol: The AI assistant needs to support the MCP protocol.
Learning curve: Basic command-line operations need to be understood.
Storage space: A large amount of log data may accumulate during long-term operation.
How to use
Install devtap
Install devtap via Go, Homebrew, or by directly downloading the binary file.
Configure AI assistant integration
Run the installation command in the project directory, configure the MCP server, and modify the project guidance file.
Install skills (optional)
Install devtap skills to allow the AI assistant to obtain build errors via the CLI when MCP is unavailable.
Start using
Run your build commands with devtap and use the AI programming assistant in another terminal.
Usage examples
Rust project development
Use devtap in a Rust project to automatically capture compilation errors and let the AI assistant fix them immediately.
Node.js project build
Capture build and test output in a Node.js project and filter to show only errors and warnings.
Long-running development server
Monitor the output of the development server and provide real-time feedback on problems to the AI assistant.
Send instructions to the AI assistant
Use devtap as a human-machine communication channel to directly send text instructions to the AI assistant.
Multi-process parallel monitoring
Monitor multiple build processes simultaneously, with each process using a different tag.
Frequently Asked Questions
Which AI programming assistants does devtap support?
How is data security ensured?
Why don't I see any output after running devtap?
How do I clean up the stored data?
Is cross-machine usage supported?
What if the MCP tool is not being called?
Related resources
GitHub repository
Source code, issue tracking, and the latest version of devtap
Go package documentation
API documentation and reference for the Go package
Model Context Protocol
Official documentation and specifications for the MCP protocol
GreptimeDB
GreptimeDB time-series database for advanced storage features
Claude Code documentation
Official usage documentation for Claude Code
GitHub Releases
Download the latest version of devtap

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
28.5K
4.3 points

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
38.2K
5 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
80.5K
4.3 points

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
24.9K
4.5 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
37.5K
5 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
70.8K
4.5 points

Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
106.4K
4.7 points

Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
55.5K
4.8 points





