"A guide to managing GitLab projects" matching MCP servers:

Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.

MCP server for GitLab REST API enabling AI agents to manage pipelines, merge requests, diffs, and local reviews.

An MCP server that integrates AI agents with Figma, enabling reading and programmatic modification of designs.

Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.

Exposes WAI-ARIA Authoring Practices Guide (APG) patterns, providing narratives, keyboard guidance, and official source code examples for accessible widgets. It includes tools for listing patterns, retrieving specific specs, and performing semantic searches via Ollama.

Enables AI assistants to query Justin's resume, including background, projects, skills, and contact details, through natural language.

Enables AI assistants to fully interact with Asana, including creating and managing tasks, projects, time tracking, and search, all through natural language.

Enables sending web push notifications and managing Pushpad resources (notifications, subscriptions, projects, and senders) through natural language, using the Pushpad API.

A Model Context Protocol server for the Quire project management platform, enabling AI assistants to securely interact with Quire projects, tasks, and data.

Enables coding agents to compose, tune, render, mix, and audit native VOCALOID3/4 projects from scratch, acting as a production bridge between intent and finished song.

Enables AI assistants to read and modify Figma designs programmatically through the Model Context Protocol.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.

Enables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.

Deterministic encode, decode, hash and convert for agents, on the same pipeline engine as the String Utility Belt web app, CLI and editor extensions: a pipeline built and checked in the browser runs unchanged from its share link. Base64/hex/URL, JWT, hashes, JSON/YAML/CSV/XML, dates and regex; tools to search, describe and run utilities or whole pipelines, and to detect input formats. Runs locally

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Enables LLMs to interact with the AT Protocol ecosystem, including Bluesky, through natural language. Supports public data access without authentication and full write operations with authentication.

Enables AI assistants to read, search, and traverse your entire reMarkable library, including handwritten notes via OCR.

A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.