"MinIO" matching MCP servers:

Governed MinIO object-storage operations — capacity, exposure-surface audit, lifecycle, and healing RCA, with guarded bucket writes, unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

A Model Context Protocol server that lets AI assistants communicate through Minionese, offering tools for chat and text transformation, reusable prompts, and resources for banana-aligned intelligence.

Enables coding agents to read Jira Cloud issues, search via JQL, and retrieve comments, attachments, and change history through a lightweight, context-efficient MCP toolset.

MCP server that serves PostHog JavaScript SDK documentation to coding agents via efficient retrieval, offering tools to query and assemble cited context for tasks like capturing custom events.

Five tiny, single-purpose MCP servers for AI agents — arXiv search, YouTube transcripts, web-to-Markdown, market quotes & FX, and a persistent memory vault. No API keys, no bloat.

Lightweight MCP server that crawls Confluence subtrees and serves cached Markdown, enabling search and retrieval of Confluence pages via MCP tools.

Enables interacting with the Lunch Money personal finance API through MCP tools for retrieving user info, transactions, and performing calculations, with minimal response sizes.

A minimal MCP server that provides a persistent DuckDB SQL engine to AI assistants, enabling natural-language querying of CSVs, Parquet, and cloud data with 12 tools and optional read-only mode.

Enables local, CPU-only image and video manipulation—such as background removal, resizing, format conversion, thumbnails, GIF creation, and trimming—through an MCP server without API keys, GPU, or paid dependencies.

Enables language models to discover and use standardized ERP tools and resources, such as querying stock, viewing products and clients, and registering sales with human confirmation for destructive actions.

Enables delegating narrow tasks such as classification, schema-based extraction, and summarization to local models running through Ollama or LM Studio, with code-validated structured outputs.

Enables AI assistants to automate WeChat Developer Tools for mini programs, allowing navigation, inspection, and manipulation of pages and components through the miniprogram-automator API.