rest-api-pipeline
claudeBuild dlt pipelines for REST APIs: find a source, scaffold the pipeline, add endpoints and incremental loading, debug it, validate the data and view it in a report. Requires dlt[hub].
8 skills · 1 MCP server
Build and deploy a minimal custom REST API pipeline to the dltHub platform after running uvx dlthub-init. Requires dlt[hub].
Plugin dlthub-init-skills from marketplace dlthub-ai-harness in dlt-hub/dlthub-ai-harness. Commands read from the repo's manifest — yesterday.
This plugin runs code on your machine — it starts local MCP servers. The exact commands are listed below; read them before installing.
deploy-minimal-ingestion-pipelineBuild and deploy a minimal custom REST API pipeline to dltHub Platform. Use when the user says "Help me build and deploy a minimal pipeline", "I've finished onboarding, now what?", or "I just ran dlthub-start and want to build my own pipeline".
dlt-workspace-mcpruns: uv run dlthub ai mcp --stdio
Build dlt pipelines for REST APIs: find a source, scaffold the pipeline, add endpoints and incremental loading, debug it, validate the data and view it in a report. Requires dlt[hub].
8 skills · 1 MCP server
Load tables from any SQLAlchemy-supported database into a destination with dlt, and tune performance with the available backends. Requires dlt[hub].
8 skills · 1 MCP server
Turn raw dlt pipeline data into a Canonical Data Model: annotate sources, build an ontology, design a Kimball-style model and write @dlt.hub.transformation functions. Requires dlt[hub].
6 skills · 1 MCP server
Shared rules, secrets handling, background agent authoring and the workspace MCP server used by the other dlthub toolkits. Requires dlt[hub].
5 skills · 1 MCP server
Add column-level checks and load metrics to dlt pipelines, run them on every load and review failures with diagnosis. Requires dlt[hub].
4 skills
Prepare and deploy your dlthub workspace and pipelines to the dltHub platform, and debug failed deployments. Requires dlt[hub].
4 skills
Agentic QE (external: maintained in proffesor-for-testing/agentic-qe, pinned to v3.15.17): a quality-engineering fleet with 11 QE agents, 9 skills, 9 commands, the agentic-qe MCP server pinned to the plugin version, and the aqe-mod guard that refuses destructive operations on AQE learning data
9 skills · 9 commands · 11 agents · 1 MCP server
5 skills + 35 modes + Material Passport pipeline. Includes v3.6.7 cross-model audit gate and v3.6.8 generator-evaluator contract.
5 skills · 16 commands · 4 agents · hooks
Automates browser interactions for web testing, form filling, screenshots, and data extraction
12 skills
The official CCXT MCP server plus the ccxt-mcp usage skill — market data, balances and opt-in trading across 100+ crypto exchanges and prediction markets, with keys kept local.
1 MCP server
Eval-gated LLM fine-tuning lifecycle (LoRA/QLoRA, DPO, GRPO/RLVR, vision SFT, quantized export). Use when fine-tuning an open-weights model end-to-end: building the eval harness first, selecting method and model, preparing data, training with Unsloth or TRL, gating checkpoints, and exporting GGUF/FP8.
10 skills · 2 commands · 3 agents
Without good data, your agent gives generic advice. Keyword research, competitor research, backlinks, and site audits. All for $10/month.
12 skills · 1 MCP server
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