Quick Start

Prerequisites

A Bedrock account with an API key
A construction drawing PDF

Set your API key:

export BEDROCK_API_KEY=sk_xxx

1. Create a Project

curl -X POST https://api.bedrock.cv/projects \
  -H "Authorization: Bearer $BEDROCK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"name": "My First Project"}'

{
  "id": "prj_01JABCD123",
  "name": "My First Project",
  "created_at": "2024-01-15T10:00:00Z"
}

2. Upload a Drawing

Upload a PDF file, then create a drawing from it.

# Create a file upload
curl -X POST https://api.bedrock.cv/files \
  -H "Authorization: Bearer $BEDROCK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "project_id": "prj_01JABCD123",
    "filename": "arch-set-rev-b.pdf",
    "content_type": "application/pdf"
  }'

{
  "id": "fil_01JABCD111",
  "upload_url": "https://storage.bedrock.cv/upload/...",
  "upload_headers": { "Content-Type": "application/pdf" }
}

# Upload the PDF to the signed URL
curl -X PUT "https://storage.bedrock.cv/upload/..." \
  -H "Content-Type: application/pdf" \
  --data-binary @arch-set-rev-b.pdf

# Create a drawing from the uploaded file
curl -X POST https://api.bedrock.cv/drawings \
  -H "Authorization: Bearer $BEDROCK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "project_id": "prj_01JABCD123",
    "file_id": "fil_01JABCD111",
    "name": "Architectural Set Rev B"
  }'

{
  "id": "drw_01JABCD222",
  "name": "Architectural Set Rev B",
  "job_id": "job_01JABCD333",
  "created_at": "2024-01-15T10:01:00Z"
}

3. Wait for Processing

Bedrock’s vision pipeline automatically splits the PDF into sheets, detects blocks, and parses features. Poll the job until it completes:

curl https://api.bedrock.cv/jobs/job_01JABCD333 \
  -H "Authorization: Bearer $BEDROCK_API_KEY"

{
  "job_id": "job_01JABCD333",
  "type": "drawing.preprocess",
  "status": "Completed",
  "created_at": "2024-01-15T10:01:00Z",
  "completed_at": "2024-01-15T10:02:30Z"
}

4. Query the Drawing Index

Your drawing is now parsed into the Drawing Index. Here are two ways to work with it:

REST API
MCP (AI Agents)

List sheets in your drawing:

curl "https://api.bedrock.cv/sheets?drawing_id=drw_01JABCD222" \
  -H "Authorization: Bearer $BEDROCK_API_KEY"

{
  "data": [
    { "id": "sht_01A", "sheet_number": "A-101", "title": "First Floor Plan", "discipline": "A" },
    { "id": "sht_01B", "sheet_number": "A-102", "title": "Second Floor Plan", "discipline": "A" },
    { "id": "sht_01C", "sheet_number": "A-501", "title": "Details", "discipline": "A" }
  ]
}

Query features — count duplex receptacles on a sheet:

curl "https://api.bedrock.cv/features?sheet_number=E-201&type=duplex_receptacle&project_id=prj_01JABCD123" \
  -H "Authorization: Bearer $BEDROCK_API_KEY"

{
  "data": [
    { "id": "ftr_01A", "type": "duplex_receptacle", "label": null, "parent_feature_id": "ftr_room201" },
    { "id": "ftr_01B", "type": "duplex_receptacle", "label": null, "parent_feature_id": "ftr_room201" },
    { "id": "ftr_01C", "type": "duplex_receptacle", "label": null, "parent_feature_id": "ftr_room202" }
  ],
  "_meta": { "total": 17 }
}

Get a feature with its relations:

curl "https://api.bedrock.cv/features/ftr_door104?expand=relations,block" \
  -H "Authorization: Bearer $BEDROCK_API_KEY"

See the full CMS API reference for all endpoints.

Connect the Drawing Index to your AI agent and query with natural language.Add to your MCP configuration:

{
  "mcpServers": {
    "bedrock": {
      "type": "http",
      "url": "https://mcp.bedrock.cv/mcp",
      "headers": { "Authorization": "Bearer sk_xxx" }
    }
  }
}

Then ask your agent:

“How many duplex receptacles are on sheet E-201?”

The agent calls query_feature and returns:

17 duplex receptacles on E-201: 4 in Room 201, 3 in Room 202, 2 in Room 203…

“What are the specs for door 104?”

The agent calls query_feature to find the door, follows the scheduled_in relation to the Door Schedule, and returns:

Door 104: 3’-0” x 7’-0”, hollow metal, 45-min fire rating, hardware set HW-3.

See the full MCP setup guide for Claude, ChatGPT, and Microsoft Copilot configuration.

Next Steps

Core Concepts

Understand the Drawing Index data model — hierarchy, features, relations, and grids.

MCP Workflows

See how AI agents chain tools to answer construction questions.

Getting Started

Core Concepts

Account

Resources

Prerequisites

1. Create a Project

2. Upload a Drawing

3. Wait for Processing

4. Query the Drawing Index

Next Steps

Core Concepts

MCP Workflows

​Prerequisites

​1. Create a Project

​2. Upload a Drawing

​3. Wait for Processing

​4. Query the Drawing Index

​Next Steps

Core Concepts

MCP Workflows

Prerequisites

1. Create a Project

2. Upload a Drawing

3. Wait for Processing

4. Query the Drawing Index

Next Steps