Feedback Hub MCP

An MCP server that lets AI assistants like Claude read and analyze the data in Feedback Hub, a feedback collection app that classifies incoming feedback with AI.

Once connected, you can ask Claude questions like:

• "How many feedback entries do we have, and what's the breakdown by type?"

• "Show me the urgent bugs."

• "What are people asking for most?"

Claude picks the right tool, queries the live database and answers in plain language, often adding its own prioritization ("#4 blocks a whole team, look at it first").

Tools

Related MCP server: Customer Service Data Analyst MCP Server

Security by design

Giving an AI access to a database deserves care. This server is built so that safety does not depend on the code being bug-free:

• Read-only at the platform level. The Cloudflare API token only has the D1 Read permission. Any attempt to change data is rejected by Cloudflare itself, even if the code or the AI tried to.

• No personal data leaves the server. Submitter email addresses are never selected from the database, so they never reach the AI's context.

• Constrained inputs. Filters only accept a fixed list of values, and every value is passed to SQL as a bound parameter (?), never concatenated into the query.

• No secrets in the repo. All credentials live in a git-ignored .env file. Only an empty template (.env.example) is committed.

Setup

Prerequisites

• A deployed Feedback Hub instance with its D1 database

• Node.js 20.12 or later

• Claude Desktop

1. Install

git clone https://github.com/aydin-omer/feedback-hub-mcp.git
cd feedback-hub-mcp
npm install

2. Create a read-only Cloudflare API token

In the Cloudflare dashboard, go to My Profile → API Tokens → Create Token and create a custom token with a single permission: Account → D1 → Read. Copy the token; it is only shown once.

3. Configure

cp .env.example .env

Fill in the three values in .env:

• CLOUDFLARE_ACCOUNT_ID: run npx wrangler whoami

• D1_DATABASE_ID: run npx wrangler d1 list and copy the ID of your Feedback Hub database

• CLOUDFLARE_API_TOKEN: the read-only token from step 2

4. Test with MCP Inspector (optional)

npx @modelcontextprotocol/inspector node src/index.js

In the browser window that opens, click Connect, then Tools → List Tools, and run get_feedback_stats.

5. Connect to Claude Desktop

In Claude Desktop, open Settings → Developer → Edit Config and add a mcpServers entry to claude_desktop_config.json. Use absolute paths; run which node to find yours:

{
  "mcpServers": {
    "feedback-hub": {
      "command": "/usr/local/bin/node",
      "args": ["/absolute/path/to/feedback-hub-mcp/src/index.js"]
    }
  }
}

If the file already contains other settings, add mcpServers next to them rather than replacing the file.

Quit Claude Desktop completely (Cmd+Q on macOS), reopen it and start a new chat. Claude reads the server list only on startup, and the tool list at the start of each chat.

Troubleshooting

• Claude doesn't see a new tool: restart Claude Desktop and start a new chat.

• Server doesn't start: run npm start in the project folder. A "Missing configuration" message means .env is missing or incomplete.

• Logs: on macOS, Claude Desktop writes the server's log to ~/Library/Logs/Claude/mcp-server-feedback-hub.log.

License

MIT