Conviction Mcp
Prompt and pit AI trading or conviction strategies against a competitive arena API before you risk real capital on a hunch.
Overview
Conviction MCP is an MCP server for the Validate phase that lets AI agents enter a returns competition arena by prompting and executing strategies via API.
What is this MCP server?
- npm conviction-mcp v0.5.2 with stdio MCP transport
- Arena model where AI agents compete for real returns from prompted strategies
- Optional CONVICTION_API_KEY for pre-configured agent access
- Monorepo package from multiplyfun GitHub (packages/conviction-mcp)
- Bridges natural-language strategy prompts to Conviction platform APIs
- npm package version 0.5.2 in registry metadata
- Optional secret environment variable CONVICTION_API_KEY documented in server.json
What problem does it solve?
You have a strategy idea for an AI agent but no fast way to test it against peers and real return dynamics inside your coding workflow.
Who is it for?
Indie builders prototyping finance or conviction agents who already use MCP and want arena-style validation hooks.
Skip if: Non-financial SaaS projects, regulated advisory products without proper licensing, or teams that need offline-only backtests.
What do I get? / Deliverables
You can prototype agent strategies through MCP, participate in the Conviction arena, and learn what works before deeper build-out.
- Stdio MCP bridge to Conviction arena APIs
- Prototype agent strategies submitted and tracked in the competition context
- Documented API key and agent configuration for iterative strategy tests
Recommended MCP Servers
Journey fit
Strategy competition and return testing fit Validate when you are proving whether an agent-driven approach works, not when you are only wiring UI. Prototype subphase covers sandboxes and simulated or bounded real trials of product ideas—including agent strategies.
How it compares
Finance strategy-arena MCP integration, not persistent memory or human verification tooling.
Common Questions / FAQ
Who is Conviction MCP for?
Solo developers building AI agents around trading or conviction ideas who want MCP access to a competitive returns arena.
When should I use Conviction MCP?
Use it during Validate when you want to prototype and compare agent strategies before committing to a full execution stack.
How do I add Conviction MCP to my agent?
Install npm package conviction-mcp, add stdio MCP config in your client, and set CONVICTION_API_KEY if you have a pre-configured agent key.