Resemble AI

io.github.resemble-ai由 GitHub 帳號 resemble-ai 發布v1.4.0更新於 Oct 30, 2026

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

已驗證Streamable HTTP可網頁執行安全與監控資料與分析媒體與設計

概覽

AI 產生的概覽

Resemble AI 官方遠端 MCP 伺服器,用於深偽與 AI 文字偵測、媒體智慧分析、浮水印以及網站 AI 代理辨識。

可以做什麼
  • 偵測公開 HTTPS 連結中的音訊、圖片或影片是否為深偽,並取得或追問已完成的偵測結果
  • 偵測 25 字以上的文字是否由 AI 生成,並查詢文字偵測結果
  • 分析媒體內容:轉錄、翻譯、講者、情緒、場景描述與不實資訊分析
  • 浮水印相關:檢查媒體是否帶有 Resemble 隱形浮水印、嵌入浮水印、追蹤音訊來源
  • 執行託管的 Detect Agent 調查(保險理賠、突發新聞、證件、文件、證據、社群內容)並讀取調查紀錄
  • 管理 Agent Detection 網站整合,查看訪客分析、工作階段紀錄與單次造訪的判定依據
適用情境
適合需要判斷媒體或文字是否由 AI 生成、加入或驗證來源浮水印,或了解網站流量中有多少來自 AI 代理而非真人的情境。
執行需求
遠端 streamable HTTP 端點,無需本機安裝。每個請求都需以 Bearer 權杖方式提供 Resemble API 金鑰。媒體必須是可公開存取的 HTTPS 連結;文字直接內嵌送出且至少 25 字。Detect Agent 執行次數受團隊額度限制。
安裝前請注意
需要提供 Resemble API 金鑰,該金鑰可存取團隊帳戶與執行額度。送出的媒體連結與文字會傳送至 Resemble 服務。Agent Detection 工具會建立與修改網站整合及可發布金鑰,浮水印工具會產生新的媒體檔案。偵測結論屬模型輸出,應連同信心分數一併說明,而非視為確定事實。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Resemble AI,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.resemble-ai%2Fresemble-mcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

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

README

Resemble AI MCP Server

[License: MIT] [Python 3.10+] [MCP]

Official MCP server exposing Resemble AI documentation as resources and tools. Connect to Cursor, Claude Code, or any MCP-compatible client to enable your coding assistant to access Resemble AI docs during development.

Overview

This is the official Resemble AI MCP server. It implements the Model Context Protocol (stdio transport) to serve documentation from docs/pages/ as queryable resources. The server aggregates docs by topic and provides full-text search across all MDX files.

What it provides:

  • Topic-based documentation aggregation (13 topics: voice-cloning, text-to-speech, agents, etc.)
  • Full-text search across all MDX documentation pages
  • OpenAPI 3.0 spec with exact request/response schemas for code generation
  • Direct page and endpoint access

Once connected, your coding assistant can query Resemble AI documentation programmatically. You can vibe code complete applications—your assistant has instant access to guides, tutorials, and exact API schemas for accurate code generation.

Quick Start

1. Clone & Install

bash
git clone https://github.com/resemble-ai/resemble-mcp.gitcd resemble-mcp
# Create virtual environmentpython3 -m venv venvsource venv/bin/activate  # Windows: venv\Scripts\activate
# Install dependenciespip install -r requirements.txt

2. Configure MCP Client

Cursor: Add to ~/.cursor/mcp.json:

json
{  "mcpServers": {    "resemble-ai-docs": {      "command": "/path/to/resemble-mcp/venv/bin/python",      "args": ["/path/to/resemble-mcp/server.py"]    }  }}

Claude Code / Claude Desktop: Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or equivalent location for your OS:

json
{  "mcpServers": {    "resemble-ai-docs": {      "command": "/path/to/resemble-mcp/venv/bin/python",      "args": ["/path/to/resemble-mcp/server.py"]    }  }}

Note: Use absolute paths. Replace /path/to/resemble-mcp with your actual path.

3. Restart Client

Restart your MCP client to load the server. Tools will be available after restart.

Available Tools

resemble_docs_lookup

Returns aggregated documentation for a topic. Accepts topic ID and returns all related pages concatenated.

Parameters:

  • topic (string, required): One of: voice-cloning, text-to-speech, speech-to-speech, speech-to-text, getting-started, voice-design, streaming, detect, agents, sdks, projects-clips, audio-tools, ssml

Returns: Markdown content with all pages for the topic.

resemble_search

Full-text search across all documentation pages. Returns matching pages with snippets.

Parameters:

  • query (string, required): Search query
  • limit (integer, optional): Max results (default: 5)

Returns: List of matching pages with titles, paths, and content snippets.

resemble_get_page

Retrieves a specific documentation page by path.

Parameters:

  • path (string, required): Page path relative to docs/pages/ (e.g., getting-started/quickstart)

Returns: Full page content in Markdown.

resemble_list_topics

Lists all available topic IDs with descriptions.

Returns: Markdown list of topics.

resemble_api_endpoint

Get detailed OpenAPI specification for a specific API endpoint. Returns exact request/response schemas, parameters, and types.

Parameters:

  • method (string, required): HTTP method (GET, POST, PUT, PATCH, DELETE)
  • path (string, required): API endpoint path (e.g., /synthesize, /voices)

Returns: Endpoint specification with schemas, parameters, and response formats.

resemble_api_search

Search the OpenAPI spec for endpoints matching a query.

Parameters:

  • query (string, required): Search query (e.g., voice, streaming, agent)

Returns: List of matching endpoints with methods, paths, and summaries.

Usage

Once configured, your coding assistant (Cursor, Claude Code, etc.) can call these tools directly. Example use cases:

Building a voice cloning app:

json
{  "name": "resemble_docs_lookup",  "arguments": { "topic": "voice-cloning" }}

Searching for streaming implementation:

json
{  "name": "resemble_search",  "arguments": { "query": "websocket streaming", "limit": 5 }}

Getting exact API schema for implementation:

json
{  "name": "resemble_api_endpoint",  "arguments": { "method": "POST", "path": "/synthesize" }}

Finding all voice-related API endpoints:

json
{  "name": "resemble_api_search",  "arguments": { "query": "voice" }}

Your assistant uses these tools automatically when you ask it to build features. For example, "build me a TTS streaming service" triggers resemble_docs_lookup for the text-to-speech topic, and may use resemble_api_endpoint to get exact request schemas for accurate implementation.

Project Structure

resemble-mcp/├── server.py               # MCP server implementation├── docs/│   └── pages/              # MDX documentation files│       ├── getting-started/    # Auth, quickstart, basics│       ├── voice-generation/   # TTS, STT, S2S│       ├── voice-creation/     # Voice cloning, recordings│       ├── agents/             # AI agents│       ├── detect/             # Deepfake detection│       └── guides/             # Step-by-step tutorials└── openapi/    └── openapi.yml         # OpenAPI 3.0 specification

Supported MCP Clients

Works with any client implementing the Model Context Protocol:

Development

The server uses stdio transport (reads from stdin, writes to stdout) as per MCP specification.

bash
# Run server directly (for testing/debugging)python server.py

Architecture:

  • Server implementation: server.py
  • Documentation source: docs/pages/ (MDX files)
  • API specification: openapi/openapi.yml (OpenAPI 3.0)
  • Topic definitions: Hardcoded in TOPICS dict
  • Search: Full-text search with scoring across docs and OpenAPI endpoints

Troubleshooting

Server not loading:

  • Verify absolute paths in MCP config
  • Ensure virtual environment is activated
  • Check mcp package is installed: pip show mcp

Tools not appearing:

  • Restart MCP client
  • Check client logs for initialization errors
  • Verify server starts without errors: python server.py

Search returns no results:

  • Use resemble_docs_lookup with topic ID for guaranteed results
  • Try broader search terms
  • Check topic list: resemble_list_topics

License

MIT License - see LICENSE for details.

Links

來源:README.md,提交 372ac08

工具

18

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.

輸入參數url必填visualizemodel_typemax_wait_secondsrun_intelligenceuse_ood_detectoruse_reverse_searchzero_retention_modeaudio_source_tracing

get_detection

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

輸入參數uuid必填max_wait_seconds

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.

輸入參數text必填thresholdmax_wait_secondszero_retention_mode

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.

輸入參數uuid必填max_wait_seconds

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.

輸入參數url必填media_typestructured_jsonmax_wait_seconds

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.

輸入參數query必填detect_uuid必填max_wait_seconds

detect_watermark

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

輸入參數url必填

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).

輸入參數url必填strengthcustom_messagemax_wait_seconds

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.

輸入參數uuid必填

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.

無需輸入參數。

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.

輸入參數url必填querypreset_id必填check_urlsmax_wait_seconds

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.

輸入參數run_id必填preset_id必填

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>.

無需輸入參數。

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().

輸入參數namedomain必填

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.

輸入參數namedomains必填site_id必填

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.

輸入參數sinceuntilsettledsite_idpage_path

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.

輸入參數pagesinceuntilsearchsettledsite_idper_pagepage_path

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.

輸入參數session_id必填include_events

版本歷史

2
  1. v1.4.0最新Oct 29, 2026
  2. v1.1.0Sep 16, 2026

評分

已滿足適用檢查項的 100%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分