"YAML" matching MCP servers:

A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files.

An MCP server for anti-money laundering (AML) compliance, including customer due diligence, transaction monitoring, and SAR filing, compliant with 6AMLD, UK MLR 2017, and FinCEN.

A Model Context Protocol server that creates tools from API configurations defined in YAML files, allowing easy integration of external APIs into an MCP ecosystem without coding.

A token-efficient, schema-aware MCP server that enables AI assistants to safely read, modify, query, and validate JSON, YAML, and TOML files with automatic schema detection and format conversion capabilities.

Enables AI assistants to query, validate, and create vCluster YAML configurations directly from GitHub, supporting version-specific queries and automatic validation.

Provides deterministic conversion between YAML and JSON formats, enabling autonomous agents to flawlessly translate complex configurations without LLM formatting errors.

Enables loading and accessing LAML (YAML-based markup language) documents from the filesystem through the Model Context Protocol.

Drop-in stdio interceptor that gates MCP tools/call requests through a YAML policy (block / require_approval / audit / budget cap) before they reach the real server. The same policy file is reused by @jamjet/claude-code-hook and @jamjet/openai-guardrail, so one rule set covers Claude Desktop, Cursor, OpenAI Agents, and custom clients.

MCP server for lossless YAML 1.2 editing by AI agents. Two tools — noyalib_get (read a value at a dotted/indexed path) and noyalib_set (write a value, preserving comments/formatting byte-for-byte). Pure Rust, streaming-first serde, JSON Schema validation. MIT OR Apache-2.0.

Local MCP server that registers restricted Python filters and runs them against local JSON, YAML, and TXT files, enabling safe data filtering and file conversion.

* taniwhaai/arai 🦀 🏠 🍎 🪟 🐧 - Policy enforcement for AI coding agents derived from existing instruction files (CLAUDE.md, .cursorrules, .windsurfrules, .github/copilot-instructions.md) — no separate YAML to maintain. Rules with prohibitive predicates (never, forbids, must_not) emit permissionDecision: deny to block tool calls in Claude Code; advisor

Provides safe, deterministic inspection, transformation, validation, and diffing of structured data (JSON, CSV, YAML, Parquet) via schema-aware MCP tools.

Automated QA for .NET microservice backends and React frontends, enabling API contract testing, UI crawling, YAML flows, and run diffing against a stage environment.

Parses Unity text-serialized .prefab, .unity, and .asset files to output only Inspector-visible data in hierarchical YAML, reducing token usage by up to 96%.

Enables image generation using Gemini native models, supporting both single prompts and batch processing via a file-based queue. It allows for detailed configuration of aspect ratios and models using YAML frontmatter across various MCP-enabled clients.

Exposes design system component documentation to LLM clients via MCP, allowing listing and retrieving component contexts from Markdown files with YAML frontmatter.

Large-file-safe JSON MCP server with 10 tools: format, validate, search, JSONPath query, deep diff, and multi-format conversion (CSV/TSV/YAML/TypeScript). Handles JSON of any size without crashing.

Enables commit-addressed editing of LinkML YAML schemas via MCP, including applying changesets and reading schemas at specific commits.

Render hierarchical system diagrams as PNGs from YAML definitions using a four-level ontology of networks, factories, machines, and nodes.

Renders a YAML CV into a one-page PDF via notboringresume.cloud, optionally generating a cover letter adapted to the resume and job offer.