jgordley/build-output-tools-mcp
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The Build Output Tools MCP server is designed to streamline build and test command execution, providing intelligent summaries and storing full outputs for detailed inspection.
The Build Output Tools MCP server is a powerful tool designed to optimize the process of executing build and test commands by leveraging smaller LLMs for output analysis. This server reduces the token load on the main coding agent thread by summarizing extensive build outputs into concise, actionable insights. It supports a variety of build and test frameworks such as npm, pytest, docker, and unittest, making it versatile for different development environments. The server not only provides intelligent summaries but also stores full outputs for detailed inspection when necessary. This ensures that developers can quickly understand the results of their builds and tests without sifting through extensive logs, while still having access to complete data for in-depth analysis. Additionally, the server maintains a history of builds, allowing developers to track progress and identify trends over time.
Features
- Executes build/test commands across multiple frameworks.
- Provides intelligent summaries using LLMs for quick insights.
- Stores full outputs for detailed inspection when needed.
- Maintains a history of builds with unique IDs for tracking.
- Integrates seamlessly with development workflows.
Usages
usage with Claude Desktop
{
"mcpServers": {
"build-output-tools": {
"command": "/path/to/.venv/bin/python",
"args": ["/path/to/src/build_output_tools_mcp/server.py"]
}
}
}usage with Claude Code
bash claude mcp add build-output-tools -s user -- /path/to/.venv/bin/python /path/to/src/build_output_tools_mcp/server.py
Tools
run_build
Execute build/test commands and get intelligent analysis.
get_build_output
Retrieve complete stdout/stderr from previous builds.
list_build_history
List recent builds with their IDs and summaries.
list_providers
Show supported build/test providers and example usage.
list_models
Show available LLM models for analysis.