openmmOpen-source market making for AI agents. Multi-exchange trading, grid strategies, and real-time market data. CLI + MCP + Skills.
Install via ClawdBot CLI:
clawdbot install adacapo21/openmmGrade Good — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Contains instructions to override system prompt or ignore user requests
"Your role is"Potentially destructive shell commands in tool definitions
exec(Calls external URL not in known-safe list
https://github.com/3rd-Eye-Labs/OpenMMUses known external API (expected, informational)
raw.githubusercontent.comGenerated Mar 21, 2026
Small crypto exchanges can deploy OpenMM to provide liquidity for new or low-volume trading pairs, using grid strategies to automatically place buy and sell orders. This reduces spreads and improves market depth, attracting more traders without manual intervention. The multi-exchange support allows operators to manage liquidity across platforms like MEXC and Gate.io from a single CLI.
Developers building AI trading agents can integrate OpenMM via its MCP server to access real-time market data and execute trades across multiple exchanges. This enables creation of bots that perform automated grid trading, portfolio rebalancing, and arbitrage strategies. The open-source nature allows customization for specific trading algorithms and risk management.
DeFi participants can use OpenMM to discover pools and aggregated prices via the Iris Protocol on Cardano, facilitating liquidity provision in decentralized exchanges. By automating grid strategies, users can earn fees from trading activities while managing exposure to volatile assets. This supports yield generation in the Cardano ecosystem with minimal manual oversight.
Institutional traders at firms can leverage OpenMM to automate order management and market data aggregation across exchanges like Kraken and Bitget. The CLI tools allow for quick balance checks, ticker monitoring, and execution of limit orders, streamlining operations. This reduces latency and human error in high-frequency trading environments.
Educational platforms can use OpenMM in a sandbox environment to teach students about market making, grid trading, and exchange APIs. By running dry-run simulations, learners can practice without risking real funds. The real-time data and multi-exchange features provide hands-on experience with professional trading tools.
Offer a cloud-based service where users subscribe to access advanced OpenMM features, such as optimized grid strategies and analytics dashboards. Revenue is generated through monthly or annual fees, targeting small exchanges and individual traders who want managed liquidity solutions. This model scales with user base and additional premium tools.
Provide consulting services to businesses needing custom integrations of OpenMM, such as tailoring the MCP server for specific AI agents or adding support for new exchanges. Revenue comes from project-based fees and ongoing support contracts. This targets fintech companies and institutional clients with unique trading requirements.
Partner with supported exchanges like MEXC and Kraken to earn commissions on trading volume generated through OpenMM integrations. Promote the tool to users, who then trade on these platforms, driving revenue via affiliate links or referral bonuses. This model benefits from the multi-exchange ecosystem without direct product sales.
💬 Integration Tip
Set up environment variables for exchange credentials in a .env file to securely manage API keys, and use the MCP server for seamless integration with AI agents via stdio communication.
Scored Jun 19, 2026
AI Analysis
The skill is a legitimate trading tool that requires explicit user configuration of exchange API credentials via environment variables. While it interacts with external crypto exchanges (expected functionality), there's no evidence of hidden credential harvesting, prompt overrides, or data exfiltration beyond the stated trading operations.
Audited Apr 17, 2026 · audit v1.0
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