MCP server

Meetsponsors Official

com.meetsponsors/mcp

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Search thousands of active YouTube sponsors and 60,000+ channels from any MCP client. Free tier.

Working at last checkVerified publisher: meetsponsors.comAbout 3,441 tokens per request once connected19 tools

Website

https://api.meetsponsors.com/mcp

At a glance

Type: MCP server
Publisher: meetsponsors.com (verified by the MCP Registry)
Status: Working at last check
Tools: 19
Token cost: About 3,441 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to Cursor Add to VS Code VS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http meetsponsors https://api.meetsponsors.com/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.meetsponsors]
url = "https://api.meetsponsors.com/mcp"

Gemini CLI

{"mcpServers":{"meetsponsors":{"httpUrl":"https://api.meetsponsors.com/mcp"}}}

Cursor

{"mcpServers":{"meetsponsors":{"url":"https://api.meetsponsors.com/mcp"}}}

VS Code

{"servers":{"meetsponsors":{"type":"http","url":"https://api.meetsponsors.com/mcp"}}}

Antigravity

agy mcp add meetsponsors https://api.meetsponsors.com/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"meetsponsors","server_url":"https://api.meetsponsors.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"meetsponsors","server_url":"https://api.meetsponsors.com/mcp"}

Tools

import_status ~108 tokens
Poll the progress of a bulk import batch by its batchId. Returns total/queued/done/failed counts plus startedAt/finishedAt timestamps. Batches expire after 7 days.
sponsor_get ~77 tokens
Get detailed information about a specific sponsor by ID. Strips raw scrape data and llm internal analysis blobs.
sponsor_mostActive ~145 tokens
Get the most active sponsors in a given period (week/month/year), optionally filtered by language. Returns compact format.
sponsor_recentCollaborations ~113 tokens
Get the most recent collaboration (one video per YouTuber) with a sponsor, sorted by publication date
sponsor_recentVideos ~104 tokens
Get the most recent sponsored videos from a sponsor, ordered by publication date
sponsor_search ~410 tokens
Search sponsors by name, description, industry tags, or filters. Returns compact results (id, name, tagline = what the brand sells in a few words, website, niches, industryTags, country, operations, medianSubscribers). Use sponsor_get for full detail on a specific sponsor.
sponsor_similar ~113 tokens
Find sponsors similar to a given sponsor based on industry tags and niches. Returns compact format.
sponsor_stats ~74 tokens
Get statistics for a sponsor: number of YouTubers, median subscribers, operations per week/month/year
sponsor_youtubers ~103 tokens
Get YouTubers who have worked with a sponsor. Returns compact format.
youtuber_add ~166 tokens
Add a single YouTuber to the database and trigger the full enrichment pipeline (tags, niches, description, similarity, sponsor detection). Returns a batchId you can poll with import_status. Prefer passing a channel ID (UCxxxxxxxxxxxxxxxxxxxxxx, 24 chars) — handles ('@xxx') and URLs work too but cost
youtuber_bulk_add ~166 tokens
Add up to 50 YouTubers in one call and trigger enrichment for each. Returns a batchId you can poll with import_status. Strongly prefer channel IDs (UCxxxxxxxxxxxxxxxxxxxxxx, 24 chars) over handles/URLs — handles cost an extra YouTube API quota point each, which depletes the daily 10k budget faster.
youtuber_fullAnalysis ~255 tokens
Agent plan only. Run sponsor detection on the ENTIRE video history of a YouTuber already in the database (not just the latest videos like youtuber_refresh), and re-check older automatic rejections with the current detection pipeline — use it when youtuber_sponsors looks incomplete for a channel with
youtuber_get ~169 tokens
Get detailed information about a specific YouTuber by their YouTube channel ID. Includes llmDescription and llmSponsorProfile (LLM-friendly summaries), lastAnalyzedAt (when sponsors were last detected on the channel — every channel is re-scanned weekly; use youtuber_refresh if it is older than 7 day
youtuber_lastActiveBiggest ~129 tokens
Get the biggest YouTubers who have been active recently (last 15 days) for a specific language. Returns compact format.
youtuber_recentSponsored ~117 tokens
Get the most recent sponsored videos from a YouTuber, with one video per sponsor (sorted by publication date)
youtuber_refresh ~170 tokens
Re-run sponsor detection on a YouTuber already in the database (latest videos). Costs 50 requests of your monthly MCP quota. Refused when the channel was analyzed less than 7 days ago — every channel is re-scanned weekly, so check lastAnalyzedAt from youtuber_get first. Runs in the background (a few
youtuber_search ~602 tokens
Search YouTubers with advanced filters: subscribers, language, niches, sponsors worked with, monthly frequency, etc. All filters combine with AND — including hasWorkedWith, which keeps only creators who worked with EVERY listed domain. For "worked with brand A OR brand B", run one search per brand (
youtuber_similar ~118 tokens
Find YouTubers similar to a given YouTuber based on content, niches, and sponsors. Returns compact format.
youtuber_sponsors ~302 tokens
Get sponsors a YouTuber has worked with, including video counts for each sponsor. Sorted by most recent sponsored video first (sortBy=lastVideo, default) or by first collaboration (sortBy=firstVideo). Paginated: use offset with limit (max 50 per page) and hasMore to walk big channels. Returns compac

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