MCP Server

The Pluggy Docs Model Context Protocol (MCP) server lets any AI agent read Pluggy's documentation, guides, API reference, changelog, recipes, and curated support Q&A directly at runtime. Instead of guessing from stale training data, your agent answers questions and writes integration code grounded in the live docs — with citations.

The server is hosted at:

https://mcp.pluggy.ai/mcp

It's a remote HTTP server: no installation, no API key. Point any MCP-compatible client at that URL and it works.

The server now lives on its own address, so it stays the same even if the documentation site later moves — https://mcp.pluggy.ai/mcp is the URL to use from here on. The previous one, https://v2.docs.pluggy.ai/api/mcp, keeps working, so anything you already set up is fine as it is.

One URL, optional sign-in — the same server for everyone:

• Without signing in → the public documentation tools (docs, API reference, changelog, recipes, Q&A).
• Signed in with your Pluggy dashboard account → the above plus your dev-portal tools — your teams, applications, connectors, items, and usage — scoped to your team. Sign-in is optional; use it anonymously for docs, or connect it to your data.

Skills vs. MCP

The MCP server gives an agent live access to Pluggy's documentation at runtime. Agent Skills give the agent the know-how — the patterns and best practices — for building with Pluggy. They work independently, and even better together.

What you can do with it#

Once connected, ask your agent to build with Pluggy and it will pull the exact, current answer instead of hallucinating:

• "How do I create a connect token and open the Connect Widget?" → grounded steps from the live guides.
• "Show me the details of the createItem endpoint." → method, path, parameters, and schemas straight from the OpenAPI spec.
• "What changed in the last release for webhooks?" → the actual changelog entry, not a guess.
• "Why is my item stuck in WAITING_USER_INPUT?" → the curated, human-verified support Q&A that answered it before.
• "Write the code to list a user's transactions with pagination." → integration code that matches the current API.

Because it reads the same content published on this site, the answers stay correct as the docs evolve — you never re-teach your agent.

Available tools#

Connect it to your tool#

Pick your agent below. Everywhere you see it, the server URL is the same: https://mcp.pluggy.ai/mcp.

Claude Code#

claude mcp add --transport http pluggy-docs https://mcp.pluggy.ai/mcp

Add -s user to make it available in every project: claude mcp add -s user --transport http pluggy-docs https://mcp.pluggy.ai/mcp.

Claude Desktop#

Settings → Connectors → Add custom connector, name it Pluggy Docs, and paste https://mcp.pluggy.ai/mcp. Or edit claude_desktop_config.json:

{
  "mcpServers": {
    "pluggy-docs": {
      "type": "http",
      "url": "https://mcp.pluggy.ai/mcp"
    }
  }
}

ChatGPT (OpenAI)#

In Settings → Connectors → Advanced → Developer mode, add a connector with the URL https://mcp.pluggy.ai/mcp. (Custom remote MCP connectors are available on ChatGPT Plus/Pro/Business/Enterprise.) In a chat, enable the Pluggy Docs connector and ask away.

OpenAI Codex CLI#

Add to ~/.codex/config.toml:

[mcp_servers.pluggy-docs]
command = "npx"
args = ["-y", "mcp-remote", "https://mcp.pluggy.ai/mcp"]

Codex talks to local (stdio) MCP servers, so mcp-remote bridges to the hosted HTTP server.

Cursor#

Add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (per-project):

{
  "mcpServers": {
    "pluggy-docs": {
      "url": "https://mcp.pluggy.ai/mcp"
    }
  }
}

VS Code (GitHub Copilot agent mode)#

One command:

code --add-mcp '{"name":"pluggy-docs","type":"http","url":"https://mcp.pluggy.ai/mcp"}'

Or create .vscode/mcp.json in your workspace:

{
  "servers": {
    "pluggy-docs": {
      "type": "http",
      "url": "https://mcp.pluggy.ai/mcp"
    }
  }
}

Windsurf#

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "pluggy-docs": {
      "serverUrl": "https://mcp.pluggy.ai/mcp"
    }
  }
}

Gemini CLI#

Add to ~/.gemini/settings.json:

{
  "mcpServers": {
    "pluggy-docs": {
      "httpUrl": "https://mcp.pluggy.ai/mcp"
    }
  }
}

Zed#

Add to your Zed settings.json:

{
  "context_servers": {
    "pluggy-docs": {
      "command": {
        "path": "npx",
        "args": ["-y", "mcp-remote", "https://mcp.pluggy.ai/mcp"]
      }
    }
  }
}

Any other MCP client#

If your client only supports local (stdio) servers, bridge to the hosted one with mcp-remote:

npx -y mcp-remote https://mcp.pluggy.ai/mcp

Clients that support remote Streamable HTTP servers can use the URL directly.

Test your setup#

Start a new chat with your agent and try:

Using the Pluggy docs MCP, how do I create a connect token and open the Connect Widget?

or

List the Pluggy API endpoints for Items and show me the details of createItem.

The agent should call the MCP tools and answer with citations from the live documentation. If nothing happens, restart the client after adding the server and confirm the URL is exactly https://mcp.pluggy.ai/mcp.

What it exposes#

The server covers everything published on this site:

• Documentation guides — concepts, quickstart, and integration guides (EN, PT, ES)
• API Reference — every endpoint from the OpenAPI spec, with parameters and schemas
• Changelog — release notes, breaking changes, and migration notes
• Recipes — step-by-step integration patterns and code examples
• Curated Q&A — real support questions answered and verified by the Pluggy team

Signed in (your Pluggy dashboard account), the same server also exposes your dev portal, scoped to your team: list your teams and applications, connectors, items, and usage stats. Your token is validated and used only to reach your own team's data — never another customer's, and never Pluggy-internal knowledge.

The documentation tools are read-only and public; the dev-portal tools require sign-in. To call the Pluggy product API directly, use the API ReferenceAPI with your own credentials.

Your own data: the dev-portal tools#

Sign in and the agent can answer questions about your integration, not only about the documentation — why an item is failing, what a webhook delivered, how much you ingested last month.

The first call asks you to sign in with the same account you use on the Dashboard, through your MCP client's normal authorization flow. There is no API key to paste, and your clientSecret never reaches the agent: the tools read the dev portal on behalf of your user, scoped to the teams that user can already see.

A session usually goes: list_teams → list_applications → select_application, and from there the data tools reuse that team and application. Asking the agent to "use my sandbox application" is enough — it makes those calls itself.

What to ask it#

Why is item 8a7c… stuck? Use the Pluggy dev portal tools.

List the webhook events my production application delivered today, and open the last
failed one.

How many transactions did we ingest last month compared with the one before?

When something does not work#

• The agent never calls the tools. Restart the client after adding the server — most only read their MCP configuration at startup — and check the URL is exactly https://mcp.pluggy.ai/mcp.
• "Not authenticated" on a dev-portal tool. The client is set to sign in only on demand; see the note above.
• The answer looks out of date. The tools read the published site, so anything not yet published is not visible to them either. Check the page itself on v2.docs.pluggy.ai.
• Your client only speaks stdio. Bridge with npx -y mcp-remote https://mcp.pluggy.ai/mcp.