Polkassembly MCP Server

Overview

The Polkassembly MCP Server bridges the gap between AI assistants and the Polkassembly governance platform by exposing a set of well‑defined API endpoints through the Model Context Protocol. Polkassembly is the primary discussion and voting hub for Polkadot and Kusama ecosystems, hosting proposals, debates, and community feedback. By wrapping these endpoints in MCP, developers can empower conversational agents to fetch real‑time proposal data, post comments, or monitor voting activity without writing custom HTTP clients.

This server solves the problem of seamless, typed access to a complex governance API for AI workflows. Instead of parsing raw JSON responses or managing authentication tokens manually, an MCP client can request a specific resource (e.g., “proposal‑details” or “vote‑summary”) and receive a structured payload ready for natural‑language generation. This streamlines the integration of governance data into chatbots, knowledge bases, or automated analysis pipelines.

Key capabilities include:

• Resource discovery: Clients can list available endpoints (e.g., , , ) and understand the expected input schema.
• Tool execution: The server supports actions such as posting a comment or casting a vote, enabling the AI to perform interactive tasks on behalf of users.
• Prompt templating: Pre‑defined prompts help the assistant ask for necessary parameters (proposal ID, comment text) in a user‑friendly manner.
• Sampling controls: Developers can fine‑tune response generation (temperature, token limits) to match the conversational style required by their application.

Typical use cases span from governance analytics—where a chatbot summarizes proposal trends—to automated community engagement, where the AI drafts and posts comments after reviewing discussion threads. In a research setting, developers can query historical voting data to feed machine‑learning models that predict future outcomes. For operational teams, the server can be wired into monitoring dashboards to alert on critical proposal milestones.

Integration is straightforward: an MCP‑enabled assistant declares the Polkassembly server as a tool, then invokes resources or tools by name. The server handles authentication with the Polkassembly API, translates request parameters into HTTP calls, and returns structured results. Because all interactions are typed, downstream components can validate responses without additional parsing logic.

What sets this MCP server apart is its domain‑specific focus on a high‑impact blockchain governance platform. It abstracts the intricacies of Polkassembly’s data model, providing developers with a ready‑to‑use interface that aligns naturally with conversational AI workflows. This reduces development time, minimizes bugs related to API misuse, and opens the door for richer, real‑time governance experiences powered by AI assistants.