# Tools

> Every listed resource, editors’ picks first. The filters below can be combined.

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Resources for DevOps / SRE or ML / AI, Tagged `data-analysis`: 13 items.

> - DevOps / SRE: Deployment, monitoring, cloud resources and reliability.
> - ML / AI: Model training, evaluation and LLM application development.

- [Scientific Agent Skills](https://hebbmind.com/ja/skill/scientific-agent-skills.md): [Skill] 166 research skills maintained by K-Dense (formerly Claude Scientific Skills), spanning bioinformatics, cheminformatics, clinical research, materials and physics, including unified access to 78 public databases such as PubChem and UniProt. Works with Claude Code, Codex and Cursor.
- [Quantitative Trading](https://hebbmind.com/ja/plugin/quantitative-trading.md): [Plugin] Quant trading plugin from the wshobson/agents marketplace: quant analyst and risk manager subagents plus backtesting and risk metrics skills for strategy backtests, portfolio optimization and risk measures like VaR, Sharpe ratio and max drawdown. Needs local Python; not investment advice.
- [Nushell](https://hebbmind.com/ja/cli/nushell.md): [CLI] Cross-platform shell built around structured data: pipelines pass tables instead of plain text, and you can open and query JSON, CSV, TOML and more directly. Default builds include nu --mcp, which serves it to agents as an MCP server.
- [Vibe-Trading](https://hebbmind.com/ja/mcp/vibe-trading.md): [MCP] Trading research agent from HKU's HKUDS whose MCP server offers 70+ tools for quotes, financials, backtesting and research across A-shares, Hong Kong and US stocks and crypto. Needs local Python; HK, US and crypto research need no API key. For research only; not investment advice.
- [Miller](https://hebbmind.com/ja/cli/miller.md): [CLI] Processes CSV, TSV, JSON and other structured data like awk, sed, cut, join and sort, but by field name, for cleaning, aggregation, format conversion and pretty-printing. The command is mlr; written in Go with no runtime dependencies.
- [Steampipe](https://hebbmind.com/ja/cli/steampipe.md): [CLI] Query cloud resources and SaaS APIs live with SQL: plugins map AWS, Azure, GCP, GitHub, Kubernetes and other services to tables you can select from directly, no ETL needed. A single binary with Postgres built in.
- [Jupyter Notebooks](https://hebbmind.com/ja/skill/jupyter-notebook.md): [Skill] Creates, edits and validates reproducible Python and SQL Jupyter notebooks: organizes cells as reports or tutorials, checks conclusions against actual output and reruns top to bottom before handoff. Maintained by OpenAI in the Data Analytics plugin of openai/plugins.
- [MATLAB MCP Server](https://hebbmind.com/ja/mcp/matlab-mcp-core-server.md): [MCP] MathWorks' official server that lets agents start your local MATLAB, write and run scripts and unit tests, and check code style and potential errors, for computing, simulation and data analysis. Needs a licensed MATLAB R2021a+ and the downloaded server binary.
- [Jupyter MCP Server](https://hebbmind.com/ja/mcp/jupyter-mcp-server.md): [MCP] Connects agents to live Jupyter notebooks: read, write, insert and execute cells and read multimodal outputs like charts, for interactive data analysis. Bring your own JupyterLab or JupyterHub; open source, maintained by Datalayer.
- [MATLAB Agentic Toolkit](https://hebbmind.com/ja/plugin/matlab-agentic-toolkit.md): [Plugin] MathWorks' official toolkit: set up the MCP server via the MATLAB installer so agents can run code, run tests and do static checks; domain skill sets for signal processing, controls, statistics and machine learning install as Claude Code plugins. Needs MATLAB R2021a+.
- [Neo4j Cypher MCP Server](https://hebbmind.com/ja/mcp/mcp-neo4j-cypher.md): [MCP] Graph database MCP server from Neo4j Labs: reads the graph schema and runs read and write Cypher queries, with read-only mode, query timeouts and response token limits. Needs a Neo4j instance with the APOC plugin enabled.
- [Elastic Agent Skills](https://hebbmind.com/ja/skill/elastic-agent-skills.md): [Skill] Elastic's official skills teaching agents to use Elasticsearch and Kibana correctly: index design, ES|QL queries, search relevance tuning, dashboards, observability troubleshooting and security alert triage. Currently a technical preview.
- [FinLab AI](https://hebbmind.com/ja/skill/finlab-ai.md): [Skill] Official FinLab quant skill: lets agents use FinLab data (mainly Taiwan stocks, plus US, Japan, Korea and Hong Kong) to write stock-picking strategies, run backtests and analyze factors. Needs a FinLab account (free tier has a daily data cap), Python 3.10+ and uv. Not investment advice.
