panini-connector-mcp

panini-connector-mcp

MCP server that lets AI coding agents (Claude Desktop, Cursor, Windsurf, Claude Code, etc.) install and verify the panini-connector SDK on a customer's self-hosted site — end-to-end, without human copy-pasting.

Companion to the wizard at panini.autoscreen.ai — same code generation, same verify flow, exposed as MCP tools an agent can call.

What it does

Exposes 4 tools over the Model Context Protocol:

Tool	What it does
install_panini_connector	Given (language, framework, storage), returns the install command + files to write + env vars to set. Handles Next.js App/Pages, Express, FastAPI, Django, Flask. Storage: Supabase, Postgres, custom DB (MySQL/Mongo/etc.), or in-memory.
verify_panini_connector	Fires all 4 signed HTTP ops (ping / create_post / update_post / delete_post) at the deployed URL. Returns per-op status + diagnostics. Cleans up its own smoke-test post.
generate_shared_secret	Returns a cryptographically-random 32-byte hex secret for SEO_CONNECTOR_SECRET.
get_envelope_schema	Returns the raw HTTP envelope contract Panini uses. For agents implementing custom handlers in languages the SDK doesn't cover (Laravel, Rails, Go, .NET, etc.).

Install (one line per client)

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "panini-connector": {
      "command": "npx",
      "args": ["-y", "panini-connector-mcp"]
    }
  }
}

Windows note: GUI apps don't inherit shell PATH. Use cmd as the command instead:

{
  "mcpServers": {
    "panini-connector": {
      "command": "cmd",
      "args": ["/c", "npx", "-y", "panini-connector-mcp"]
    }
  }
}

Restart Claude Desktop. You should see 4 new tools available.

Cursor

Settings → Cursor Settings → MCP → Add new MCP server:

{
  "mcpServers": {
    "panini-connector": {
      "command": "npx",
      "args": ["-y", "panini-connector-mcp"]
    }
  }
}

Windsurf

Edit ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "panini-connector": {
      "command": "npx",
      "args": ["-y", "panini-connector-mcp"]
    }
  }
}

Claude Code (CLI)

claude mcp add panini-connector -- npx -y panini-connector-mcp

Example agent workflow

Once registered, prompt your AI:

"Install the panini-connector on this Next.js site. It uses Supabase — the table is blog_posts and posts render at /blog/[slug]."

The agent will:

• Call install_panini_connector with language=node, framework=next_app, storage=supabase, existing_table=blog_posts, url_template=https://.../blog/{slug}
• Read the returned install_command and run npm install panini-connector in your project
• Write app/api/seo-connector/route.ts with the returned file content
• Call generate_shared_secret and prompt you to add SEO_CONNECTOR_SECRET=<value> to your hosting env vars
• Prompt you to redeploy
• Once deployed, call verify_panini_connector with your URL + the secret
• Report the result: 4 green ✓s means the round-trip works and you're ready to paste URL+secret into the Panini dashboard

Tool reference

install_panini_connector

Input:
  language: 'node' | 'python'
  framework: 'next_app' | 'next_pages' | 'express' | 'fastapi' | 'django' | 'flask'
  storage: 'supabase' | 'postgres' | 'custom_db' | 'memory'
  existing_table?: string           // default 'blog_posts'
  url_template?: string             // default 'https://yoursite.com/blog/{slug}'

Output:
  install_command: string           // shell command to run in project root
  files: [{ path, content, language }]  // files the agent writes
  env_vars: string                  // env vars to set on hosting
  post_install_note?: string        // gotchas (bodyParser: false, etc.)
  verify_command: string            // manual CLI verification command

Framework/language pairing:

• node → next_app | next_pages | express
• python → fastapi | django | flask

verify_panini_connector

Input:
  url: string                       // https://mysite.com/api/seo-connector
  secret: string                    // exact SEO_CONNECTOR_SECRET value
  timeout_ms?: number               // default 10000

Output:
  ok: boolean
  url: string
  ops: [{
    op: 'ping' | 'create_post' | 'update_post' | 'delete_post'
    status: 'pass' | 'fail'
    http_status?: number
    response_body?: unknown
    error?: string
  }]
  summary: string

generate_shared_secret

Input: {}
Output: { secret: string, length_bytes: 32 }

get_envelope_schema

Input: {}
Output: {
  http_method: 'POST'
  request_headers: { ... }
  request_body_shape: { ... }
  response_success: { ... }
  response_ping: { ... }
  response_errors: { ... }
  replay_window_seconds: 300
  hmac_pseudocode: string
  laravel_example: string
}

Use this when the customer's stack isn't Node or Python — the returned contract is enough for an agent to hand-implement the connector in any language.

Running locally / debugging

# Test the server directly (JSON-RPC over stdio)
npx panini-connector-mcp
# then type an MCP initialize request; server responds on stdout, logs on stderr

# Or with the MCP inspector
npx @modelcontextprotocol/inspector npx panini-connector-mcp

License

MIT.