mcpField
D
Docsie

Docsie

Local
github.com/LikaloLLCMemory & Knowledge0Updated 29w ago

About Docsie

Docsie is a remote MCP server that turns video URLs into structured Markdown documentation for Claude users. It supports document types such as user guides, SOPs, product docs, policies, and blog posts, with OAuth2 authentication.

Key features

  1. 01Generate structured docs from video URLs
  2. 02Support YouTube, Loom, Vimeo, and MP4 sources
  3. 03Choose from multiple document types
  4. 04Check processing status and retrieve results
  5. 05List document types and quality tiers

Use cases

  1. 01Creating a user guide from a video
  2. 02Turning a recording into an SOP
  3. 03Producing product documentation or a blog post from video
  4. 04Checking the status of a documentation job

MCP support

Docsie exposes `analyze_video`, `check_job_status`, and `list_doc_types` as tools to MCP clients. It uses Streamable HTTP and OAuth2 Authorization Code with PKCE.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"docsie-dokuta": {
"command": "npx",
"args": [
"-y",
"mcp-remote"
],
"env": {
"API_KEY": "<API_KEY>"
}
}
}
}
Run commandnpx -y mcp-remote
Environment variables to set
API_KEYSecret

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmmcp-remote

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Docsie Video-to-Docs MCP Server

Remote MCP server for Anthropic's Connectors Directory. Converts videos into structured documentation using Dokuta AI.

What It Does

Users on Claude can:

  1. Submit a video URL (YouTube, Loom, Vimeo, direct MP4, etc.)
  2. Choose a doc type (user guide, SOP, product docs, policy, blog)
  3. Get structured markdown documentation back

Free tier: Videos up to 5 minutes are processed free. Longer videos require a Docsie account with AI credits.

Architecture

Claude → POST https://mcp.docsie.io/mcp (Bearer token)
              │
              ├─→ Docsie /o2/ (OAuth2 token validation)
              ├─→ Dokuta API (video analysis)
              └─→ Docsie /api/internal/mcp/ (credit deduction)
  • Transport: Streamable HTTP (MCP spec)
  • Auth: OAuth2 Authorization Code + PKCE via Docsie's /o2/ provider
  • Runtime: Python 3.12 + FastMCP + Starlette + uvicorn

MCP Tools

ToolDescription
analyze_videoSubmit a video URL for documentation generation
check_job_statusPoll for progress and retrieve completed results
list_doc_typesList available doc types and quality tiers

Local Development

cd mcp-server

# Install dependencies
pip install -e .

# Configure environment
cp .env.example .env
# Edit .env with your Dokuta API key and Docsie internal URL

# Run
uvicorn app.main:app --reload --port 8000
Test endpoints
# Health check
curl http://localhost:8000/health

# OAuth metadata
curl http://localhost:8000/.well-known/oauth-authorization-server

# MCP tool listing (via MCP protocol)
curl -X POST http://localhost:8000/mcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":"1","method":"tools/list","params":{}}'

Environment Variables

VariableDescriptionDefault
MCP_DOCSIE_BASE_URLDocsie public URL (for OAuth metadata)https://app.docsie.io
MCP_DOCSIE_INTERNAL_URLDocsie internal URL (for API calls)http://docsie-web:8080
MCP_DOKUTA_API_URLDokuta video analysis APIhttps://app.videodokuta.com/api/v1
MCP_DOKUTA_API_KEYDokuta API key(required)
MCP_MCP_INTERNAL_API_KEYShared secret for Django internal endpoints(required)
MCP_OAUTH2_CLIENT_IDOAuth2 client ID for the MCP app(required)
MCP_FREE_TIER_MAX_SECONDSMax free video duration in seconds300

Deployment (Kubernetes)

Docker images are built and pushed automatically via GitHub Actions on push to main.

# Deploy with Helm (secrets managed via Doppler)
helm upgrade --install mcp-staging helm/docsie-mcp/ \
  -n mcp \
  --set image.tag=v2026.04.06.01 \
  --set doppler.token=$DOPPLER_SERVICE_TOKEN

Django Side Setup

1. Add internal API key to Django settings

In your .env or environment:

MCP_INTERNAL_API_KEY=your-shared-secret-here
2. Register OAuth2 Application

In Django admin at /o2/applications/register/:

  • Name: Claude MCP Connector
  • Client type: Public
  • Authorization grant type: Authorization code
  • Redirect URIs: (provided by Anthropic during directory registration)
  • Skip authorization: Yes
3. Internal endpoints (already wired)
  • GET /api/internal/mcp/user-context/ — token validation + user info
  • POST /api/internal/mcp/deduct-credits/ — credit deduction

Anthropic Connectors Directory Submission

To submit to the directory, you'll need:

  1. MCP Server URL: https://mcp.docsie.io/mcp
  2. OAuth2 metadata URL: https://mcp.docsie.io/.well-known/oauth-authorization-server
  3. Company name: Docsie Inc.
  4. Description: "Convert videos into structured documentation using AI. Submit a video URL and get back a user guide, SOP, product docs, or blog post."
  5. Logo: Docsie logo (SVG/PNG)
  6. Privacy policy: https://www.docsie.io/privacy-policy/
  7. Terms of service: https://www.docsie.io/terms-of-service/

Submit at: https://console.anthropic.com/dashboard/connectors

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.