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lewing/helix.mcp

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CLI tool and MCP server for investigating .NET CI failures in Helix and Azure DevOps

概览

An increasingly inaccurately named CLI and MCP server for AI agents investigating .NET CI/CD failures across Helix and Azure DevOps. hlx works as a standalone CLI — dnx lewing.helix.mcp (zero-install) or dotnet tool install -g lewing.helix.mcp. See the CLI reference. AI agents investigating CI failures in dotnet repos (runtime, sdk, aspnetcore, etc.) hit two problems: 1. A single Helix console log can be megabytes. The Azure DevOps build timeline returns hundreds of records. Dumping this into a context window wastes tokens and drowns the signal. 2. When multiple agents — or the same agent across tool calls — inspect the same build, each one repeats the same API calls and downloads. - Tools like helix_search and azdo_search_log search in place and return only matching lines with context — agents never download a full log. helix_status returns structured failure summaries instead of raw JSON.

README

以下为原文 README 节选,完整内容请查看原文。

helix.mcp

An increasingly inaccurately named CLI and MCP server for AI agents investigating .NET CI/CD failures across Helix and Azure DevOps.

No MCP needed. hlx works as a standalone CLI — dnx lewing.helix.mcp (zero-install) or dotnet tool install -g lewing.helix.mcp. See the CLI reference.

Built with Squad — meet the squad.

Why?

AI agents investigating CI failures in dotnet repos (runtime, sdk, aspnetcore, etc.) hit two problems:

  1. Raw APIs return too much data. A single Helix console log can be megabytes. The Azure DevOps build timeline returns hundreds of records. Dumping this into a context window wastes tokens and drowns the signal.
  2. Every agent starts from scratch. When multiple agents — or the same agent across tool calls — inspect the same build, each one repeats the same API calls and downloads.

hlx solves both:

  • Return less, return better. Tools like helix_search and azdo_search_log search in place and return only matching lines with context — agents never download a full log. helix_status returns structured failure summaries instead of raw JSON. Default tail limits (500 lines), filter parameters (failed by default), and maxMatches caps keep responses focused.
  • Cache everything, share across processes. A local SQLite cache sits between agents and the APIs. Different MCP server instances (one per IDE window/terminal) share the same cache, so the second agent to inspect a job gets instant results. Smart TTLs track job lifecycle — running jobs cache briefly (15–30s), completed jobs cache for hours.

Zero config — public dotnet CI works out of the box. Install and go.

Context-Efficient Design

Every tool is designed to minimize token consumption in agent context windows:

Technique How it helps
Tail limits helix_logs and azdo_log return the last N lines (default 500), not the full log
Complete collection on demand CLI list commands such as azdo test-runs --all and azdo test-results --all populate complete-list cache keys for deterministic scanner snapshots while MCP defaults stay capped
Pattern search helix_search and azdo_search_log search outside agent context and return matching lines with configurable context — no full ingestion
Failure-first defaults helix_status, azdo_timeline, azdo_test_results default to showing only failures
Structured JSON Failure summaries, test results, and timeline data come pre-parsed — no agent-side text extraction
Batch operations helix_batch_status checks up to 50 jobs in one call; helix_find_files scans N work items instead of N+1 API calls
在 GitHub 查看完整 README

安装

This server does not publish a one-line install command.

Open the repository installation guide 新手?先看 mcpskill.org 教程 →