Local MCP capabilities provider for Expo
Nothing to run from here
Resemble AI is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
18
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
Resemble AI: deepfake detection, media intelligence, and watermarking actions, plus docs tools.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http resemble-ai-mcp https://mcp.resemble.ai/mcp
# 2 — ask your agent for something these tools do
# detect_deepfake, get_detection, detect_ai_text and 15 more
Resemble AI costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
RAAll 1 server
resemble-ai1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
Claude Codedeclared by this listing
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http resemble-ai-mcp https://mcp.resemble.ai/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it answers at its publisher’s own address: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it writes
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
What you approve
18 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
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). mod
| Parameter | Type | Required | Notes |
|---|---|---|---|
| url | string | yes | — |
| run_intelligence | boolean | no | — |
| audio_source_tracing | boolean | no | — |
| visualize | boolean | no | — |
| use_reverse_search | boolean | no | — |
| use_ood_detector | boolean | no | — |
| zero_retention_mode | boolean | no | — |
| model_type | string | no | — |
| max_wait_seconds | integer | no | — |
Fetch a detection by UUID, polling until it completes (bounded). Use after detect_deepfake when a long job exceeded its wait budget.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| uuid | string | yes | — |
| max_wait_seconds | integer | no | — |
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 A
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | — |
| threshold | number | no | — |
| zero_retention_mode | boolean | no | — |
| max_wait_seconds | integer | no | — |
Fetch a text detection by UUID, polling until it completes (bounded). Use after detect_ai_text returned status 'processing' - typically a cold start.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| uuid | string | yes | — |
| max_wait_seconds | integer | no | — |
Analyze media for structured intelligence: transcription, translation, language, speaker info, emotion, scene description, abnormalities, and misinformation analysis. media_type: auto | audio | video | image.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| url | string | yes | — |
| media_type | string | no | — |
| structured_json | boolean | no | — |
| max_wait_seconds | integer | no | — |
Ask a natural-language question about a COMPLETED detection (e.g. 'how confident is the model that this is fake?'). Returns the grounded answer.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| detect_uuid | string | yes | — |
| query | string | yes | — |
| max_wait_seconds | integer | no | — |
Check whether media at a public HTTPS URL carries a Resemble invisible watermark (audio-first; per-channel verdict for audio).
| Parameter | Type | Required | Notes |
|---|---|---|---|
| url | string | yes | — |
Embed an invisible Resemble provenance watermark into media (audio-first) and return the watermarked media URL. strength 0.0-1.0 (image/video only).
| Parameter | Type | Required | Notes |
|---|---|---|---|
| url | string | yes | — |
| strength | number | no | — |
| custom_message | string | no | — |
| max_wait_seconds | integer | no | — |
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| uuid | string | yes | — |
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.
No parameter schema on file.
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| preset_id | string | yes | — |
| url | string | yes | — |
| query | string | no | — |
| check_urls | string | no | — |
| max_wait_seconds | integer | no | — |
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| preset_id | string | yes | — |
| run_id | string | yes | — |
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>.
No parameter schema on file.
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| domain | string | yes | — |
| name | string | no | — |
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| site_id | integer | yes | — |
| domains | array | yes | — |
| name | string | no | — |
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 helpfu
| Parameter | Type | Required | Notes |
|---|---|---|---|
| site_id | no | — | |
| settled | string | no | — |
| page_path | string | no | — |
| since | string | no | — |
| until | string | no | — |
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.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| site_id | no | — | |
| settled | string | no | — |
| page_path | string | no | — |
| since | string | no | — |
| until | string | no | — |
| search | string | no | — |
| page | integer | no | — |
| per_page | integer | no | — |
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 attack
| Parameter | Type | Required | Notes |
|---|---|---|---|
| session_id | integer | yes | — |
| include_events | boolean | no | — |
Free
$0 forever
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Resemble AI or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
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Alert at 80% · then the tool returns a normal MCP error
Used this month: —
—Grade not published
No rule-by-rule report on file for this release
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither: the repository linked on this page is where this record was collected from, not a copy of what the address serves, so it is not graded in its place. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 1.1.0.
1.1.0
undated
latestNo release note was published with this version.
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no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish Resemble AI can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
No reviews yet
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.