Resemble AI

io.github.resemble-ai由 GitHub 账号 resemble-ai 发布v1.4.0更新于 Oct 30, 2026

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

已验证Streamable HTTP可网页运行安全与监控数据与分析媒体与设计

概览

AI 生成的概览

Resemble AI 官方远程 MCP 服务器,用于深度伪造与 AI 文本检测、媒体智能分析、水印以及网站 AI 代理识别。

可以做什么
  • 检测公开 HTTPS 链接中的音频、图片或视频是否为深度伪造,并获取或追问已完成的检测结果
  • 检测 25 词以上的文本是否由 AI 生成,并查询文本检测结果
  • 分析媒体内容:转录、翻译、说话人、情绪、场景描述与虚假信息分析
  • 水印相关:检查媒体是否带有 Resemble 隐形水印、嵌入水印、追踪音频来源
  • 运行托管的 Detect Agent 调查(保险理赔、突发新闻、证件、文档、证据、社交内容)并读取调查记录
  • 管理 Agent Detection 网站集成,查看访客分析、会话记录与单次访问的判定依据
适用场景
适合需要判断媒体或文本是否由 AI 生成、添加或核验来源水印,或了解网站流量中有多少来自 AI 代理而非真人的场景。
运行要求
远程 streamable HTTP 端点,无需本地安装。每个请求都需以 Bearer 令牌方式提供 Resemble API 密钥。媒体必须是可公开访问的 HTTPS 链接;文本直接内联提交且至少 25 词。Detect Agent 运行次数受团队配额限制。
安装前请注意
需要提供 Resemble API 密钥,该密钥可访问团队账户与运行配额。提交的媒体链接和文本会发送至 Resemble 服务。Agent Detection 工具会创建和修改网站集成及可发布密钥,水印工具会生成新的媒体文件。检测结论属于模型输出,应连同置信度一并说明,而非当作确定事实。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Resemble AI,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.resemble-ai%2Fresemble-mcp/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "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

来源: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.

输入参数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.

输入参数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.

输入参数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.

输入参数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.

输入参数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.

输入参数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).

输入参数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).

输入参数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.

输入参数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.

无需输入参数。

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.

输入参数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.

输入参数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>.

无需输入参数。

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().

输入参数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.

输入参数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.

输入参数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.

输入参数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.

输入参数session_id必填include_events

版本历史

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

评分

已满足适用检查项的 100%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通必需25 分
  • 已声明认证方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分