Manifold Markets MCP Server

Overview

The Manifold Markets MCP Server bridges the gap between AI assistants and the rich ecosystem of Manifold Markets, a platform for creating, trading, and analyzing prediction markets. By exposing the full breadth of Manifold’s REST API through a well‑structured MCP interface, the server lets developers embed market intelligence directly into conversational agents. This integration unlocks a new class of AI workflows where assistants can not only retrieve market data but also orchestrate trades, manage liquidity, and coordinate collective intelligence—all while maintaining the type safety and validation guarantees that MCP clients expect.

What problem does it solve? In traditional setups, a developer must write custom API wrappers and handle authentication, rate limits, and error handling for each market operation. The MCP server abstracts these concerns behind a declarative tool system, allowing an assistant to issue high‑level commands such as or . This reduces boilerplate, minimizes the risk of mis‑authenticating requests, and ensures that every interaction is validated against Zod schemas before reaching the Manifold API. The result is a reliable, repeatable interface that can be leveraged by multiple assistants or integrated into larger data pipelines without duplicating logic.

Key capabilities are grouped into intuitive tool categories. Market creation and management tools let users launch new prediction markets, add answers to multiple‑choice questions, or revert resolutions—actions that traditionally require a deep understanding of Manifold’s permissions model. Interaction tools such as , , and bounty management enable social collaboration, allowing assistants to surface trending markets or reward insightful commentary. Trading operations expose the full lifecycle of a bet: placing, canceling, selling shares, and providing or withdrawing liquidity. Finally, information‑retrieval tools (, , , ) give assistants granular visibility into market state, user profiles, and portfolio performance.

Real‑world scenarios that benefit from this MCP server include:

• Automated market monitoring: An assistant can watch a set of markets, trigger alerts when liquidity drops below a threshold, or automatically place hedging bets.
• Collective intelligence workflows: Teams can use bounties to crowdsource analysis; the assistant awards rewards when a contribution meets specified criteria.
• Portfolio management: Developers can build AI‑driven dashboards that track positions, calculate implied probabilities, and suggest optimal trades based on market sentiment.
• Educational tools: Instructors can create bespoke prediction markets for classroom projects, with the assistant guiding students through market mechanics.

Integration is straightforward: once the MCP server is running and configured, any MCP‑compatible client (Claude Desktop, Cline, or custom agents) can call the exposed tools. The server handles authentication via an API key, enforces role‑based permissions, and surfaces informative error messages. Because the tool definitions are typed and validated, developers can rely on compile‑time guarantees that an assistant will never send malformed requests. This tight coupling between the AI’s intent and the market’s capabilities makes the Manifold MCP Server a powerful enabler for sophisticated, data‑driven conversational experiences.