"A guide to writing for publication" matching MCP servers:

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

Enables an AI agent to host a shared folder or join an invite link as a participant in a collaborative editing session, reading, editing, and writing the files the room shares. Runs the same sync engine and wire protocol as editor clients, so an agent and a person or another agent converge on the same documents and see each other's changes.

Universal HTTP 402 Micropayment Protocol & Autonomous Economic Settlement Engine for AI Agents on Base L2.

Answers why a specific number in a Chinese listed company moved — margins, cash flow, inventory, management commentary, policy impact — by reading filed reports and IR transcripts and returning figures with the document and announcement number attached. It deliberately refuses price, valuation, and recommendation queries, returning a "gone_by_design" error instead.

A client-side MCP proxy that injects OAuth 2.0 bearer tokens or API keys into MCP requests, enabling MCP clients to connect to OAuth/API-key-protected MCP servers like Amazon Bedrock AgentCore Gateway. It automatically fetches and refreshes credentials using AgentCore Identity or static values.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables searching and retrieving content, module information, and Twig template snippets from a-blog cms via its GET API.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Lets an AI assistant read call and message history, send texts and picture messages, reach Phone Book contacts by name, and — once switched on — place calls run by a voice agent, all limited to the phone numbers the user ticks. Hosted remotely with OAuth sign-in, so nothing needs to be installed locally.

Enables agents to break high-level business objectives into dependency-ordered sub-task graphs and then directly generate the finished deliverables, such as financial spreadsheets, executive presentations, and analytical reports. It runs as a zero-dependency Python MCP server over JSON-RPC stdio, adding deterministic authorization, role-boundary validation, and telemetry.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

Provides Figma design context to AI agents, enabling code generation, design system integration, and canvas manipulation through MCP.

Connects AI coding assistants to Anima Playground, Figma designs, and design systems, enabling handoff of designs to production code.

Enables MCP clients such as GitHub Copilot, Codex, Claude... to explore a SQL Server 2017+ database read-only: databases, schemas, tables, views, procedures, functions, indexes and dependency graphs, plus filtered, grouped, sampled and paginated queries capped by row limits.

Thin MCP server that enables AI agents to generate video, image, and audio content via the Deepy API using a personal API key, with safe generation flow and no business logic.

Enables querying of a locally pinned snapshot of the Education-to-Workforce Indicator Framework — 99 indicators and 11.8M observations — to browse questions, describe metrics, resolve places, and fetch or rank data across national, state, county, and district levels.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

Well-designed PDFs from a single prompt. Describe what you need, get a professional document.

Open end-to-end encrypted messaging protocol and MCP server (a4a-mcp) that gives AI agents a cryptographic address (apub1...) to exchange messages, tasks, and signed agreements directly across NAT without port forwarding.

MCP Server for Apache Pinot

An implementation of Model Context Protocol (MCP) server for Argo CD.

Enables Cursor IDE to interact with Tealfabric platform, allowing management of webapps, processes, and documents through natural language.

Manage a fleet of OPNsense firewalls from an AI agent, inside guardrails it can't drive around. MCP server for central management of OPNsense firewall fleets. 129 tools across devices, config sync, tasks, schedules, templates, backups and remote consoles - destructive actions confirmation-gated, MCP-issued tokens lifetime-bounded, backup and storage secrets excluded from the toolset entirely.

Connects MCP clients to a telephony account so users can manage phone numbers, SIP accounts, routing, SMS, calls, and billing in plain language. It exposes search, schema lookup, and execute tools to run permitted API operations, with confirmation required for paid or destructive actions.

Enables agents to discover available still-image animation models, obtain credit quotes without charge, submit one explicitly approved generation job, and poll the resulting short clip.

What is PandaDoc MCP? PandaDoc MCP (Model Context Protocol) server connects AI agents directly to PandaDoc's document workflow — creating, sending, and tracking contracts and agreements without leaving your AI client. How to use PandaDoc MCP? To use PandaDoc MCP, connect your PandaDoc account, provide the required API credentials, and configure the appropriate MCP client.

Enables AI assistants to directly control and interact with the Unreal Editor through natural language, allowing tasks such as spawning actors, building levels, creating materials, and running Python scripts.

Connects AI assistants to xyOps through Streamable HTTP, exposing tools for events, jobs, tickets, alert invocations, monitoring snapshots, and servers with API-key-scoped access.

Java based Model Context Procotol (MCP) Server for JDBC