Oraclaw
Let your coding agent optimize decisions, run simulations, score options, and analyze graphs without building a separate analytics stack.
Overview
Oraclaw is an MCP server for the validate phase that gives agents seventeen sub-25ms decision tools for optimize, simulate, predict, score, and graph workflows.
What is this MCP server?
- 17 MCP tools spanning optimize, simulate, predict, score, and graph analytics
- Sub-25ms responses suited to tight agent loops
- 11 tools on the free tier with no API key required
- Optional ORACLAW_API_KEY unlocks premium solvers, VaR/CVaR, forecasting, and anomaly detection
- stdio npm package @oraclaw/mcp-server v1.4.1
- 17 MCP tools documented
- 11 tools on free tier without API key
- Sub-25ms latency claim
Community signal: 8 GitHub stars.
What problem does it solve?
Agents guess at tradeoffs because spinning up solvers, simulators, and scoring pipelines inside a chat session is too heavy and slow.
Who is it for?
Indie builders validating pricing and feature bets who want quantitative what-if calls inside the agent without a separate analytics product.
Skip if: Teams that only need static dashboards or who do not want any optional paid API tier for advanced solvers.
What do I get? / Deliverables
Your agent can run structured what-if analysis and scoring in milliseconds while you lock scope, pricing, and rollout choices.
- Agent-callable optimize, simulate, predict, score, and graph tool results
- Eleven-tool free-tier decision workflows without secrets
- Premium solver and risk metrics when API key is configured
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Journey fit
Solo builders use decision intelligence hardest when choosing pricing tiers, feature tradeoffs, and rollout paths before committing to build. Pricing and scope decisions map directly to optimize, simulate, predict, and score tools in the MCP surface.
How it compares
MCP decision-intelligence toolkit, not a hosted BI dashboard or a single planning skill.
Common Questions / FAQ
Who is Oraclaw for?
Solo builders and small teams shipping with AI coding agents who need fast optimization, simulation, and scoring during validation and planning.
When should I use Oraclaw?
Use it when comparing pricing models, rollout paths, or risk scenarios and you want the agent to call structured tools instead of hand-waving.
How do I add Oraclaw to my agent?
Register the stdio MCP server package @oraclaw/mcp-server in Claude Code, Cursor, or another MCP client; set ORACLAW_API_KEY only if you need premium tools.