"A guide to developing Chrome extensions" matching MCP servers:

Exposes PICO XR building blocks as MCP tools, enabling AI agents to programmatically configure XR scenes for PICO devices through idempotent, non-destructive operations.

Enables AI coding assistants to control and inspect a live Chrome browser through Chrome DevTools. Provides browser automation, performance analysis, debugging capabilities, and network request monitoring.

A Model Context Protocol (MCP) server for Chrome Enterprise Premium that exposes DLP rules, content detectors, connector policies, browser telemetry, and license management as MCP tools, enabling any MCP-compatible AI agent to inspect and configure a Chrome Enterprise environment.

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.

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.

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.

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 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.

Enables MCP-compatible editors to orchestrate test runs, debug failures, analyze visual regressions, run accessibility audits, and manage test cases through natural language.

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.

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.

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.

Enables product search, price comparison, and price history analysis across 6 European marketplaces (DE, AT, GB, FR, IT, ES).

Enables searching government awards through the Sell to State API by proxying JSON-RPC to the live HTTP MCP endpoint, requiring an API key.

Lightweight project management for teams and AI agents.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

A companion MCP server for writing applications on Reddit's developer platform (Devvit). Provides tools and resources to assist with developing Reddit apps through natural language interactions.

Enables AI agents to interact with the Roark API by writing and executing TypeScript SDK code in an isolated sandbox, with built-in documentation search to guide those tasks.

Enables agents to look up countries, regions, cities and districts and to retrieve the recommended areas to stay in each, including who each area suits, why, and links to the corresponding guide pages on doalu.com. It works from public static guide data with no API key or account.

Provides a remote MCP server with four tools to list, search, and execute actions across 500+ integrated apps, using OAuth and platform-specific knowledge packages to guide agents.

Enhances LLM responses by grounding them in official Google Maps Platform documentation and code samples via MCP tools for developing applications.