Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add makifbaysal/tasktrooper --skill data-mcp-toolsgit clone --depth 1 https://github.com/makifbaysal/tasktrooperWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/makifbaysal/tasktrooper/data-mcp-tools)<a href="https://agentmods.dev/skills/makifbaysal/tasktrooper/data-mcp-tools"><img src="https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/data-mcp-tools/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/makifbaysal/tasktrooper/data-mcp-tools"><img src="https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/data-mcp-tools.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00060 | $0.01660 |
| Opus 5.5 | $0.00024 | $0.00664 |
| Sonnet 5.5 | $0.00012 | $0.00332 |
| Haiku 4.5 | $0.00006 | $0.00166 |
Grade A, and why
data-mcp-tools scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data MCP Tools
Overview
TaskTrooper can connect optional MCP servers that make data work faster: a live Jupyter kernel, DuckDB, dbt, MLflow, Hugging Face search and Postgres. They are disabled by default; a person enables them in Settings → MCP servers. They are conveniences on top of the workspace, never a replacement for it: the repository's code and its test suite remain the deliverable and the evidence.
Core principle: a server is available only if its tools are in your tool list right now. If they are not, use the CLI equivalent and carry on — never stop a task, and never ask a person to install or enable a server mid-task.
1. Detecting availability
Look at your tool list. Tools from a server carry its id in the name — mcp_duckdb_… in TaskTrooper's own runtime, mcp__duckdb__… in a CLI runtime. Tool names differ between server versions; read the descriptions in your tool list rather than assuming a name from this skill. A server whose tools are absent is not connected for this run, whatever the repository's docs say.
2. The servers
| Server id | What it gives you | Use it for | Fallback without it |
|---|---|---|---|
jupyter |
read, insert, edit and execute cells in a running local JupyterLab | looking at data interactively, checking a notebook runs cell by cell | uv run jupyter nbconvert --execute, papermill, or a script |
duckdb |
SQL over Parquet/CSV/DuckDB files, in-memory by default | EDA, profiling (SUMMARIZE), reconciling a result two ways |
duckdb CLI or uv run python -c "import duckdb; ..." |
dbt |
lineage, compile, list, show, test, run, build for the project | finding a model's parents and children, compiling SQL, running tests on the dev target | the dbt CLI with the same commands |
mlflow |
experiments, runs and registered models from the tracking server (ML tool set) | finding the current champion and its metrics to compare your candidate against | a short script with mlflow.MlflowClient |
huggingface |
model search on the Hub | finding a pretrained model and its exact revision | the Hub website docs or huggingface_hub in a script |
postgres |
read-only SQL against a configured Postgres | inspecting a source table's shape and row counts | psql with the repository's dev connection |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 80 lines · 60 tokens per session scan A 849cc76b9e8b
data-mcp-tools is a skill published in the GitHub repository makifbaysal/tasktrooper (113 stars, last pushed yesterday), licensed Apache-2.0. It adds 60 tokens to every session and 1,660 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-09.
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