gtm-mcp
Operate Google Tag Manager via MCP. Handles OAuth, resource discovery, and CRUD operations for tags, triggers, and variables directly from your LLM agent.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
530 skills found
Operate Google Tag Manager via MCP. Handles OAuth, resource discovery, and CRUD operations for tags, triggers, and variables directly from your LLM agent.
Manage Jules (Google's async AI coding agent) directly from your terminal. Create, monitor, and interact with Jules coding sessions, approve plans, and handle feedback loops across repositories.
Automates the submission workflow for lading performance optimizations, including branch management, git commits, and PR creation.
Automates invoice and receipt organization for tax preparation by parsing files, extracting financial data, renaming documents, and filing them into a structured directory system.
Dialectical reasoning and adversarial coding agent for MCP-enabled editors, forcing LLMs to resolve internal contradictions for higher quality outputs.
Evidence-based debugging for Python, Node.js, and Java applications using runtime execution traces and diagnostic MCP tools.
Generate professional Product Requirements Documents (PRD) and structure features for autonomous development cycles.
Expert systematic test design using BVA, equivalence partitioning, decision tables, and combinatorial testing to maximize coverage and minimize redundancy.
An AI-powered TestOps platform and MCP server providing automated failure analysis, RCA matching, and intelligent test orchestration for CI/CD pipelines.
Neuropixels neural recording analysis toolkit. Provides end-to-end pipelines for SpikeGLX/OpenEphys data, Kilosort4 spike sorting, motion correction, quality metrics, and AI-assisted curation.
A microworld operating system for LLM-based agent living memory, transforming filesystems into navigable rooms and code into habitable worlds.
Preserve successful Python code executions as reusable tools within the gentools package structure, utilizing Pydantic models for structured output and type-safe interfaces.