Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| optimize_banditB | Multi-Armed Bandit (UCB1/Thompson/ε-Greedy). Select the best option from a set — optimal explore/exploit tradeoff. <1ms. |
| optimize_contextualB | Contextual Bandit (LinUCB). Context-aware selection — learns which option works best in which situation. |
| optimize_cmaesB | CMA-ES continuous optimization. Tune parameters, calibrate models. 10-100x more efficient than grid search. |
| solve_constraintsA | LP/MIP/QP optimization (HiGHS). Budget allocation, scheduling, resource planning. Provably optimal. |
| solve_scheduleB | Optimal task scheduling with energy matching. Assigns tasks to time slots maximizing productivity. |
| analyze_graphC | Graph analytics: PageRank, Louvain communities, shortest path, bottleneck detection. |
| analyze_riskC | Portfolio risk: VaR/CVaR with correlation matrices. Monte Carlo simulation. |
| score_convergenceC | Multi-source agreement scoring. How much do different signals/sources agree? |
| predict_forecastB | Time series forecasting (ARIMA / Holt-Winters). Predict future values with confidence intervals. |
| detect_anomalyB | Anomaly/outlier detection (Z-score / IQR). Sub-millisecond. |
| plan_pathfindB | A* pathfinding with k-shortest paths (Yen's algorithm). Optimal routing. |
| simulate_montecarloB | Monte Carlo simulation. 5K iterations in ~1ms. Risk quantification, scenario analysis. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |