Wren AI MCP
Overview
The Wren AI MCP connects your AI agent to Wren AI so you can query your data, generate SQL, build charts, and get business insights using natural language — right from the tools you already use.
How It Works
Once connected, your AI agent can talk to your Wren AI project through a set of built-in actions: asking end-to-end questions, generating and running SQL, creating charts, and summarizing results. You install it once per platform (claude.ai, Claude Desktop, or Claude Code), and the companion analyst skill teaches your agent how to use it well.
Before You Begin
Before installing, make sure the following prerequisites are in place:
-
Enable the MCP toggle in your Wren AI project. Go to Project settings → MCP connection and turn on the toggle to allow external AI clients to connect via MCP.

-
Use a company (organization) account with custom connector permission enabled. If you're on Claude's Team/Enterprise plan, your workspace admin must enable the Add custom connectors permission for your account. Without it, you won't see the "Add custom connector" option in Claude, and you also won't be able to authorize the app on first connect.

Claude
1. claude.ai (Web) and Claude Desktop (chat/cowork/code)
Add MCP connector + create skill. Auth is handled via OAuth.
Step 1 — Add MCP Connector:
-
Go to Customize → Connectors → Add custom connector

-
Give a name to your mcp
-
URL: Copy your project MCP url in wrenai.
-
Auth: OAuth (you'll be redirected to log in with your Wren AI account)

-
Log in with your Wren AI account.

-
Authorize the app.

Step 2 — Upload Skill:
- Open Customize → Skills → Create a skill → Upload a skill
- Upload
web/claude/wrenai-analyst/SKILL.md
Generate the skill files locally:
git clone https://github.com/canner/wrenai-mcp.git && cd wrenai-mcp && ./setup --host web
2. Claude Code (CLI)
Claude Code's HTTP transport auto-discovers OAuth and hangs if the server advertises /.well-known/oauth-authorization-server. The stdio proxy bypasses this.
# Step 1: Clone the repo
git clone https://github.com/canner/wrenai-mcp.git
cd wrenai-mcp
# Step 2: Add MCP server (stdio proxy with API key)
# Replace {node_path} with your Node.js >= 20 binary (e.g. ~/.nvm/versions/node/v20.20.1/bin/node)
# Replace {your_project_id} and {your_api_key} with your Wren AI credentials
cat > .mcp.json << 'EOF'
{
"mcpServers": {
"wrenai": {
"type": "stdio",
"command": "{node_path}",
"args": [
"{absolute_path_to_repo}/mcp-proxy.mjs",
"https://cloud.getwren.ai/api/mcp/{your_project_id}",
"{your_api_key}"
]
}
}
}
EOF
# Step 3: Restart Claude Code
# Step 4 (optional): Install the data analyst skill
/install canner/wrenai-mcp
Generate an API key in your Wren AI project settings.
Done. Try /wrenai-analyst tell me about my data.
ChatGPT
Add MCP connector + set up custom instructions. Auth is handled via OAuth.
Step 1 — Enable Developer Mode & Add MCP Connector:
- Go to Settings → Apps & Connectors → Advanced settings
- Enable Developer Mode
- Back to Apps & Connectors, click Add → Add MCP server
- Name:
wrenai - URL:
https://app.getwren.ai/api/mcp/{your_project_id} - Auth: OAuth (you'll be redirected to log in with your WrenAI account)
Step 2 — Add Custom Instructions:
- Go to Settings → Personalization → Custom Instructions
- Paste the content from
web/chatgpt/wrenai-analyst-skill.md
Generate the skill content locally:
git clone https://github.com/canner/wrenai-mcp.git && cd wrenai-mcp && ./setup --host chatgpt
See ChatGPT Developer Mode & MCP docs for details.
Row-Level Security Compatibility
Currently, the Wren AI MCP does not support Row-Level Security (RLS). Support for RLS is planned for a future release.
Available Skills
setup-wrenai-mcp— One-time setup that connects your agent to a Wren AI instance.wrenai-analyst— Data analyst skill for SQL, charts, and insights from natural language.