Resemble AI MCP Server

by resemble-ai Your server? Claim it

answering

Resemble AI is answering right now. Last checked 11 min ago. It exposes 18 tools. Last commit 28 Oct 2026.

Resemble AI: deepfake, AI-text, and site agent detection, Detect Agents, intelligence, watermarks.

Uptime history 91 days of history · worst day 47%

91 days agonow

50.0%

Uptime 24h

91 of 182 checks

Tools

read from the server

317 ms

Response time

average over 24h

Stars

last commit 28 Oct 2026

What changed 13

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 23 September 2026. No other catalogue keeps this.

24 Sep a tool description was rewritten agent_detection_create_site

23 Sep 11 tools appeared agent_detection_create_site, agent_detection_get_analytics, agent_detection_get_session and 8 more

23 Sep a tool changed version

What the code does

We read the source, 4 d ago · tools taken from the live server · rules 995398eba69f

Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

Page loads a third-party script web/index.html:74

<script async src="https://porter-api-prod.onrender.com/static/gate.js" data-resemble-key="pk_live_xvCzaNfK0Wk924qiOGuSeESs" data-resemble-endpoint="https://app.resemble.ai/api/v2/agent_detection/telemetry"></script>

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

This code can reach further than it looks

We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 11 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add resemble-mcp --transport http https://mcp.resemble.ai/mcp

Settings → Connectors → Add custom connector, then paste this address

https://mcp.resemble.ai/mcp

~/.codex/config.toml

[mcp_servers.resemble-mcp]
url = "https://mcp.resemble.ai/mcp"

.cursor/mcp.json

{
  "mcpServers": {
    "resemble-mcp": {
      "url": "https://mcp.resemble.ai/mcp"
    }
  }
}

.vscode/mcp.json

{
  "servers": {
    "resemble-mcp": {
      "type": "http",
      "url": "https://mcp.resemble.ai/mcp"
    }
  }
}

This server publishes 1 more address. The block above uses the one we reach during checks; the full list is under Endpoints below, and the author may intend a particular one for your client.

Available tools 18

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

agent

agent_detection_create_site

Create an Agent Detection integration for a website and return its publishable key (pk_live_...) and the script snippet to install. domain is the site's domain, e.g. example.com. If the team already has an integration for that domain, the existing one is returned instead of a duplicate. The publishable key is safe to put in a public web page: it only sends telemetry, only from the listed domains. Never put the Resemble API key in a page. Paste the snippet into the <head> of every page to cover; the page can then listen for the 'resemble:verdict' event or call ResembleAgentDetection.onVerdict().

agent_detection_get_analytics

Summarise who is visiting a website: people vs AI agents. Returns totals (visits, decided, agents, people, agent_share, gated), counts per visitor class (human, computer_use_agent, browser_automation, scripted_client), and breakdowns by page, day, and network. Use this to show how much traffic comes from agents and which pages they use, so the site can be made easier for helpful agents and protected from harmful ones. Filters are optional: site_id (one integration), settled ('human' or 'agent'), page_path, and since/until as ISO 8601 times. agent_share is agents / decided visits, or null when nothing is decided yet.

agent_detection_get_session

Get one website visit and the evidence behind its verdict: the feature vector it was decided from, plain-language observations, and each model read. When the visit was recorded, the raw event stream is available; it is omitted unless include_events is true, and then capped at the first 200 events. The verdict is advisory: it comes from browser signals, which a determined attacker can fake.

agent_detection_list_sessions

List individual website visits, newest first, each with its verdict (settled: human, agent, or null while still open), visitor_class, p_person, the page, referrer, user agent, and duration. Same filters as agent_detection_get_analytics plus a free-text search. per_page max 100.

agent_detection_list_sites

List this team's Agent Detection integrations. Agent Detection tells a website whether each visitor is a person or an AI agent (for example a personal assistant browsing on someone's behalf). Each integration is one website, with the domains its publishable key works on and the one-line script snippet to paste into the site's <head>.

agent_detection_update_site

Replace the list of domains an Agent Detection integration's publishable key is valid on (for example to add a staging or www host), and optionally rename it. domains replaces the whole list, so include every domain to keep; at least one is required.

detect

detect_ai_text

Detect whether TEXT (an essay, email, post, review, comment, article) was written by an AI language model. Needs at least 25 words: shorter text comes back as prediction 'uncertain' with no model call - concatenate several messages from the same author to reach the minimum. Returns prediction ('ai' | 'human'), confidence (how sure the model is of that prediction; it is NOT an AI probability, so 'human' at 0.95 means strongly human), and the full result. Only the first ~400 words are read; chunk longer documents. A result can take several minutes when the model is cold or jobs are queued - if status is still 'processing' when the wait budget ends, resume with get_text_detection(uuid). Detection is probabilistic, not proof of authorship.

detect_deepfake

Detect whether media (audio, image, or video) at a public HTTPS URL is a deepfake / AI-generated. Polls to completion and returns the verdict label, confidence score, and full result. Optional flags add media intelligence, audio source tracing, visualization, reverse image search (images), out-of-distribution detection, and zero-retention (auto-delete media after analysis). model_type: auto | image | talking_head.

detect_watermark

Check whether media at a public HTTPS URL carries a Resemble invisible watermark (audio-first; per-channel verdict for audio).

get_detect_agent_run

Fetch a persisted Detect Agent investigation by run_id, including its full event transcript. Use after run_detect_agent_investigation reported timed_out, or to re-read an earlier investigation.

list_detect_agents

List the managed Detect Agents — investigators that wrap detection in a multi-step workflow ending in a written assessment. Returns each agent's preset_id plus this team's run allowance (free_runs_remaining, entitled), which is worth checking before starting a run.

run_detect_agent_investigation

Run a managed Detect Agent investigation against media at a public HTTPS URL and return its verdict. preset_id is one of: investigate_social_content, review_insurance_claim, verify_breaking_news, verify_document, verify_evidence, verify_id (confirm with list_detect_agents). query states the investigation objective; check_urls adds URLs for the agent to check. Consumes a run of the team's allowance. `label`/`score` are the Detect evidence and are the only basis for an authenticity claim; `verdict` is the agent's written assessment. If timed_out is true the investigation is still running server-side — retrieve it later with get_detect_agent_run.

analyze

analyze_media

Analyze media for structured intelligence: transcription, translation, language, speaker info, emotion, scene description, abnormalities, and misinformation analysis. media_type: auto | audio | video | image.

apply

apply_watermark

Embed an invisible Resemble provenance watermark into media (audio-first) and return the watermarked media URL. strength 0.0-1.0 (image/video only).

ask

ask_about_detection

Ask a natural-language question about a COMPLETED detection (e.g. 'how confident is the model that this is fake?'). Returns the grounded answer.

detection

get_detection

Fetch a detection by UUID, polling until it completes (bounded). Use after detect_deepfake when a long job exceeded its wait budget.

text

get_text_detection

Fetch a text detection by UUID, polling until it completes (bounded). Use after detect_ai_text returned status 'processing' - typically a cold start.

trace

trace_audio_source

Get the audio source-tracing report for a detection (which AI platform generated the fake audio). Only available when detection ran with audio_source_tracing and labeled the audio fake.

Endpoints

URL	Transport	State	Latency	Checked
https://mcp.resemble.ai/mcp	streamable-http	answering	254 ms	11 min ago
https://mcp.resemble.ai/sse	sse	answering	265 ms	12 min ago

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Resemble AI — questions

Answers built from our own checks of this server.

What can Resemble AI do?

It exposes 18 tools, read directly from the server on our last check. Among them: agent_detection_create_site, agent_detection_get_analytics, agent_detection_get_session, agent_detection_list_sessions, agent_detection_list_sites, agent_detection_update_site and 12 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →

What is Resemble AI mostly used for?

Its tools cluster around agent and detect. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.

Is Resemble AI working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 182 checks got a reply (50.0%), average response time 317 ms. The bar chart above shows every period we have measured.

How do I connect Resemble AI?

Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does Resemble AI need an API key?

No. Resemble AI completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 18 of them are readable on this page. This is what we observed, not what the docs claim.

How fast is Resemble AI?

It answers our handshake in 317 ms on average, which is faster than 45% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.

Is Resemble AI open source?

The code is open source: it is published under the MIT licence, written in Python and 2 stars on GitHub. The licence covers the code in the repository, not the hosted service at mcp.resemble.ai, which runs on its operator's own terms.