Pinterest MCP Server Pricing 2026

There are three different Figma MCP servers and the install command on most listings belongs to the one Figma no longer leads with, so start with which you are choosing. **Figma's recommended server is now the hosted remote one at `https://mcp.figma.com/mcp`** — nothing to install, OAuth in the client, attached with `claude mcp add --transport http figma https://mcp.figma.com/mcp`. It is also the only one with the write and cross-file tools (`use_figma`, `generate_figma_design`, `generate_diagram`, `create_new_file`, `search_design_system`, asset upload and download). **The Dev Mode desktop server ships inside the Figma Desktop app** — enable it in Dev Mode (Shift+D) from the MCP server section of the inspect panel and the app opens a local endpoint at `http://127.0.0.1:3845/mcp`. Figma's docs now describe the desktop server as being for specific organisation and enterprise cases and recommend the remote one instead. Because it runs in the app, it reads whatever you have selected on the canvas: exact colors, typography, spacing, auto-layout constraints, component variants, and — the part a token-based reader cannot do — your Code Connect mappings, so it emits your component names rather than generic divs. It requires a Dev or Full seat on a paid plan and the desktop app must be open. The repository linked here is `figma/mcp-server-guide`, Figma's own setup guide; Figma does not publish the server's source. **The community alternative is Figma-Context-MCP by GLips** (15,500+ stars), installed as `npx figma-developer-mcp --figma-api-key=YOUR_FIGMA_ACCESS_TOKEN`. It authenticates with a Personal Access Token from Figma Settings → Personal Access Tokens and calls the REST API, so it needs no desktop app, works headlessly in CI, and can read any file your account can open — including from a free plan. It exposes the document JSON, node lookup by ID, component listing, text extraction, and rendered-image download. The practical split: pick the official server when design-to-code fidelity and Code Connect matter and you are already paying for Dev Mode; pick GLips when you need automation, a free plan, or a machine with no Figma app installed. Both let an assistant translate a frame into accurate React, Tailwind, or plain HTML/CSS instead of guessing from a screenshot.

There is no official SendGrid MCP server, and that is the first thing worth knowing if you searched for one. Twilio owns SendGrid and does publish an official MCP server at twilio-labs/mcp, but that server is generated from Twilio's own Public API specs and covers none of SendGrid's v3 email endpoints — connecting it will not give an assistant a way to send an email or touch a contact list. Twilio's own developer blog acknowledges the gap by publishing a walkthrough on building a SendGrid MCP server yourself rather than shipping one. This entry therefore tracks the most established community implementation, Garoth/sendgrid-mcp (TypeScript, 29 stars), which wraps the SendGrid v3 Marketing API. Its tool surface is broader than most email servers: contact management (list_contacts, add_contact, delete_contacts, get_contacts_by_list), list management (list_contact_lists, create_contact_list, delete_list, add_contacts_to_list, remove_contacts_from_list), sending (send_email for one-off transactional mail with optional dynamic-template data, and send_to_list which creates a SendGrid Single Send against one or more list IDs), dynamic templates (create_template, list_templates, get_template, delete_template), plus get_stats, validate_email, list_verified_senders and list_suppression_groups. Those last two exist because SendGrid rejects sends from unverified senders and requires either a suppression_group_id or a custom_unsubscribe_url on a Single Send, so an agent has to look both up before it can complete a campaign. The README is explicit that only v3 APIs are supported — legacy templates will not work. Install is from source: git clone, npm install, then point your client at the built entrypoint with SENDGRID_API_KEY in the environment. Two cautions. The npm package named sendgrid-mcp is a different project (deyikong/sendgrid-mcp, 3 stars, which does offer a READ_ONLY mode) — do not assume npx installs the repo described here. And this server exposes delete_contacts, delete_list and delete_template, which are irreversible against a live marketing database; scope the API key narrowly rather than granting full access.

The YouTube MCP Server by Zubeid Hendricks connects AI assistants to the full YouTube Data API v3, letting Claude search videos, pull transcripts, manage content, and run analytics without leaving the conversation. It is one of the most complete community YouTube MCP servers, exposing tools across several areas: video management (search by keyword, retrieve metadata, get statistics, and list a channel's uploads), transcript retrieval (fetch full captions for any public video for summarization or Q&A), channel operations (look up channel details, subscriber and view counts, and recent activity), playlist tools (list and inspect playlist contents), Shorts creation workflows, and advanced analytics for creators tracking performance. Authentication uses a single YOUTUBE_API_KEY obtained free from the Google Cloud Console by enabling the YouTube Data API v3 — read-heavy operations fit comfortably inside the daily quota. Install globally with npm as zubeid-youtube-mcp-server, run it directly with npx (no install required), or add it through Smithery for one-click Claude Desktop setup; a Docker image is also provided for HTTP transport. The YouTube MCP Server is ideal for content research, competitive analysis, transcript-based summarization, and automated creator workflows — Claude can, for example, find the top videos on a topic, fetch their transcripts, and synthesize a briefing in a single pass.

Marcel Marais's Spotify MCP Server is a lightweight TypeScript bridge between AI assistants and the Spotify Web API, letting Claude control playback and search a listener's library through natural language. It exposes tools for searching tracks/albums/artists/playlists, controlling playback (play, pause, skip, queue management), reading and modifying the current queue, and browsing a user's playlists and saved library. Authentication uses standard Spotify OAuth (client ID/secret from the Spotify Developer Dashboard) with a one-time login flow to obtain a refresh token, after which the server runs locally via the MCP stdio transport. Typical use: ask Claude to "queue up some upbeat workout music" or "what's currently playing," and it calls the Spotify API directly rather than requiring the user to switch to the Spotify app.

Exposes Cloudinary's media upload, transformation, AI analysis, management, optimization and delivery.

The official ElevenLabs MCP server (elevenlabs/elevenlabs-mcp) connects AI assistants like Claude Desktop, Cursor, Windsurf, and OpenAI Agents directly to ElevenLabs' text-to-speech and audio-processing APIs. Once installed, an AI client can generate natural-sounding speech from text in dozens of voices and languages, clone a voice from a short audio sample, design and save new synthetic voices to a personal voice library, transcribe spoken audio with automatic speaker diarization, isolate vocals from background noise, and compose layered soundscapes (e.g. "a thunderstorm in a dense jungle with animals reacting") from a text prompt. It also exposes ElevenLabs' Conversational AI agent-creation tools, so a client can spin up a voice agent with a defined persona and have it answer questions in character. Install via PyPI/uv with `uvx elevenlabs-mcp` and an `ELEVENLABS_API_KEY` from the ElevenLabs dashboard — the free tier includes 10k credits/month, enough for testing. Optional environment variables (`ELEVENLABS_MCP_BASE_PATH`, `ELEVENLABS_MCP_OUTPUT_MODE`) control whether generated audio is saved to disk, returned as base64-encoded MCP resources for containerized/serverless environments, or both, and `ELEVENLABS_API_RESIDENCY` supports enterprise data-residency requirements. With 1,450+ GitHub stars, it is the most widely adopted way to give an AI coding assistant real audio-generation capabilities without hand-rolling API calls.