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What you’ll do

  1. Create a project board
  2. Add 3 resources (a YouTube URL, some text, a link)
  3. Search the board
  4. Ask AI a question grounded in your content

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Option A: Using Claude Code (MCP)

If you’ve set up MCP, just talk naturally: 
> Create a ChatGrid board called "Backend Project"

> Add this YouTube video to the board: https://youtube.com/watch?v=abc123

> Add these notes to the board: "We use PostgreSQL with pgvector
  for embeddings. Connection pooling via PgBouncer. See db/README
  for schema migrations."

> Add this blog post to the board: https://blog.example.com/postgres-performance-tips

> Search the board for connection pooling

> Based on the board, how should I configure PgBouncer for serverless?
That’s it. Five prompts, and you have a searchable knowledge base.

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Option B: Using the API

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Prerequisites

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Create a board

curl -X POST https://api.chatgrid.ai/v1/boards \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"name": "Backend Project"}'
Save the board_id from the response.

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Add a YouTube video

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/documents/vectorize \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://youtube.com/watch?v=abc123"}'
The transcript is extracted and vectorized automatically.

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Add text notes

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/documents/vectorize \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "content": "We use PostgreSQL with pgvector for embeddings. Connection pooling via PgBouncer. See db/README for schema migrations.",
    "metadata": {"source": "architecture-notes"}
  }'

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/documents/vectorize \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://blog.example.com/postgres-performance-tips"}'

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Search the board

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/documents/search \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query": "connection pooling", "limit": 3}'

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Ask AI a question

curl -X POST https://api.chatgrid.ai/v1/boards/{boardId}/chats/{chatId}/messages \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "content": "Based on the board, how should I configure PgBouncer for serverless?",
    "stream": false
  }'
The AI answers using your board’s content as context — not generic knowledge.

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Next steps

Team Knowledge

Share a board across your team

MCP Workflow

Use ChatGrid in Claude Code for real debugging workflows