"An overview or guide to GitHub Actions" matching MCP servers:

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

A MCP server that bridges LLMs with GitHub repository management, enabling automated analysis of pull requests, issue management, tag creation, and release management through natural language.

Connects AI agents to ROS 2 robots via rosbridge, enabling observation, inspection, and control of robot topics, services, and actions through natural language.

An MCP server that enables AI assistants to read, create, and manage issues, repositories, and releases on Gitea, Forgejo, or Codeberg instances via personal access tokens.

A governance layer for MCP servers that classifies tools by risk, enforces agent permissions, lets safe tools earn autonomy through a track record, and keeps an audit trail. Requires human approval for irreversible actions and provides blast radius context.

An enterprise workflow intelligence MCP server that reconstructs events into live workflow state, detects bottlenecks with deterministic rules, and provides evidence-based explanations and actions.

A transparent proxy that intercepts high-risk tool calls and requires OTP-based human approval before they can be executed. It acts as a configurable circuit breaker between AI agents and target MCP servers to prevent unauthorized or dangerous actions.

Query PainSpotter to discover validated business opportunities and trending pain points mined from Reddit, Hacker News, and Product Hunt.

A personal memory engine and MCP server that stores durable facts in markdown files managed via git, enabling hybrid search (lexical + semantic) through an MCP interface for persistent context across LLM sessions.

Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.

An MCP server that lets Claude analyze your TradingView charts by reading the window and taking screenshots, with no write tools or trade execution.

An open-source MCP server for live Apple App Store competitor research, enabling AI agents to search apps, fetch metadata, compare competitors, and retrieve reviews and top charts as structured JSON.

Enables AI assistants to query, analyze, and discover FileMaker database schemas via OData v4, with pandas-powered analytics for efficient data summaries.

An MCP server that provides AI agents with ICP Triangulation Framework™ for scoring prospects across firmographics, behaviors, and growth signals, plus RFM analysis and pipeline health scoring, with optional HubSpot integration.

Enables AI assistants to render 3D models from OpenSCAD code, generating single views or multiple perspectives with full camera control. Supports animations, custom parameters, and returns base64-encoded PNG images for seamless integration.

AI-powered incident management MCP server that enables investigation, root cause analysis, and response actions for production incidents using mocked data for demo purposes.

Enables AI assistants to interact with Intervals.icu fitness tracking and wellness data, allowing users to fetch, filter, and group activities or health metrics. It provides structured summaries of workouts and physical well-being through natural language queries.

MCP server that enables cloud models (like Gemini/Claude) to delegate coding tasks to a local llama.cpp server, preserving cloud usage limits through an AI-powered code review loop.

Enables management of Kylas CRM lead operations, including creating leads, searching and filtering records, and resolving user, product, or pipeline IDs. It provides specialized tools for monitoring idle leads and accessing lead schema instructions through natural language.

Provides policy-based access control, incident tracking, and compliance monitoring to govern AI agent behavior. It enables organizations to enforce security rules and maintain audit trails by validating agent actions against trust levels and pattern-based policies.