FrameForge ChatGPT Integration
Enables ChatGPT to generate images, videos, and scenes through FrameForge, and open the full FrameForge experience, with secure OAuth-based authentication.
README
FrameForge ChatGPT Integration
Separate MCP + widget integration service for the FrameForge product. The public SaaS remains https://frameforger.com.
Architecture
ChatGPT -> https://chatgpt.frameforger.com/mcp -> this integration service -> FrameForge backend -> FrameForger.com
The service is intentionally separate from the main FrameForge web app. It does not contain FrameForge generation logic; it exposes ChatGPT-safe MCP tools and forwards authenticated requests to the existing backend.
MCP tools
generate_image-> FrameForgegenerateImagegenerate_video-> FrameForgegenerateVideogenerate_scene-> FrameForgegenerateSceneopen_frameforge-> opens the full FrameForge experience at FrameForger.com
All generation tools are marked as mutating, non-destructive, open-world operations. open_frameforge is read-only and idempotent.
Authentication
Public launch is configured for OAuth 2.1 resource-server behavior.
The service exposes:
GET /.well-known/oauth-protected-resource- per-tool OAuth
securitySchemes mcp/www_authenticatechallenges for unauthenticated tool calls- JWT signature, issuer, audience, expiry, and scope verification when
OAUTH_ISSUERandOAUTH_JWKS_URLare configured
Use an established OAuth identity provider that supports the MCP authorization requirements and PKCE. Do not launch publicly with ALLOW_UNVERIFIED_BEARER=true.
The preferred backend mode is FRAMEFORGE_BACKEND_AUTH_MODE=forward, which forwards the linked user's bearer token to the FrameForge backend. This only works when the FrameForge backend recognizes tokens from the same issuer. If a separate identity provider is used, add a trusted server-side account-mapping gateway before enabling production generation.
Environment
Copy .env.example into your hosting provider's secret/environment settings.
Required for production:
MCP_PUBLIC_ORIGIN=https://chatgpt.frameforger.comFRAMEFORGE_API_BASE=<authenticated FrameForge gateway/base URL>OAUTH_ISSUER=<authorization server issuer>OAUTH_JWKS_URL=<authorization server JWKS URL>OAUTH_AUDIENCE=https://chatgpt.frameforger.com
Local development
npm install
npm start
Health endpoint:
curl http://localhost:8787/healthz
MCP endpoint:
http://localhost:8787/mcp
For local ChatGPT testing, expose the server over a public HTTPS tunnel and add the tunneled /mcp URL in ChatGPT Developer Mode.
Deployment
A Dockerfile and render.yaml are included. A suitable production deployment should:
- run Node 20+ behind HTTPS;
- map
chatgpt.frameforger.comto the service; - keep OAuth and backend credentials in the hosting provider's secret store;
- preserve streaming requests to
/mcp; - route
/healthzto health checks; - log request IDs, latency, backend status codes, and sanitized errors without logging bearer tokens.
Submission package
submission.json contains the proposed listing name, short description, MCP URL, starter prompts, five positive review tests, and three negative review tests.
Before submitting publicly, verify that these URLs exist and accurately describe FrameForge data handling:
- website:
https://frameforger.com - privacy policy
- terms
- support/contact page
Also complete OpenAI developer/business identity verification in the same organization that submits the plugin/app.
Validation status
Completed in this build:
- Node syntax check (
npm run check) - static MCP contract review
- OAuth protected-resource metadata route added
- tool-level OAuth security schemes added
- JWT verification path added
- Docker/Render deployment files added
- submission manifest added
Not completed in this environment:
- dependency installation (network install timed out)
- live MCP Inspector run
- end-to-end OAuth login
- live FrameForge generation call
- ChatGPT Developer Mode connection
Those require a reachable OAuth provider, production/test FrameForge backend URL, and deployed HTTPS endpoint.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。