# ScoreCompute > Specialized Rust computation tools for AI assistants. Public alpha. Website: https://scorecompute.com/ MCP endpoint: https://scorecompute.com/mcp Transport: MCP Streamable HTTP. No API key required for this bounded public alpha. Use MCP initialize and tools/list to discover the current schemas and limits. Version 0.3.0 exposes 18 tools: 12 independently callable computation tools and 6 optional capability and mission tools. Direct engine calls never require the composer. ## Direct computation tools - simulate_pi: seeded Monte Carlo, CPU or NVIDIA CUDA, Wilson confidence interval. - optimize_tasks: exact 0/1 task selection under an integer time budget. - simulate_plan: uncertainty simulation for the selected task durations. - compute_orbit: ideal two-body Keplerian orbit, not an observational ephemeris. - verify_shadows: solar position and shadow geometry under supplied assumptions. - check_ephemeris: approximate Sun/Moon position against a claimed observation. - audit_statistics: GRIM/GRIMMER arithmetic checks under the stated assumptions. - analyze_kinematics: angular speed and distance hypotheses, no identification of an object. - check_shadow_track: temporal shadow consistency under a solar model. - solve_equilibrium: Kuhn poker strategy via self-play. - analyze_chess_game: comparison with Stockfish; not evidence of cheating. - screen_wash_trading: trade-pattern screening; not proof of manipulation. ## Optional native mission tools - list_capabilities: inspect the 12 tool contracts, units, assumptions, backend and composition readiness. Optional exact theme filter; unknown themes return an empty list. Only the scheduling pair is currently composable. - plan_mission: validate a robust scheduling request and preview candidate budgets, engine-call and sample bounds, or explicit blockers, without executing engines. - build_robust_plan: compare up to three task selections in native Rust using optimize_tasks and, only when necessary, simulate_plan. Select the highest-value examined candidate that meets the requested success target under the stated model. Mission inputs require items, budget (integer minutes) and uncertainty (0 to 0.5). Defaults: min_success_rate 0.95, samples 10000 per candidate, seed 42, max_candidates 3, duration_model independent_uniform, allowed_tools [optimize_tasks, simulate_plan]. Candidates use nominal, 10% and 20% time reserves. Limits: 32 tasks, budget 1440 minutes, 20000 samples per candidate, 3 candidates. Unsupported duration models or missing required tool permissions produce blockers. Only approved local tools are supported, with no external commands or destinations. The native executor validates the integer-minute handoff, skips simulation when an exact worst-case bound suffices, and reuses identical selections within the same mission. Otherwise it uses fixed seeded Monte Carlo and simultaneous 95% Hoeffding error bounds across the examined family. A result is inconclusive if no candidate's lower bound meets the target; selected is then null. This is a conditional result under independent uniform duration variation, not a forecast guarantee or a globally optimal robust schedule over every possible selection. MCP progress messages prefixed SC_MISSION_EVENT: contain actual native event JSON. The entire mission is one composite MCP call. Its internal engine calls are native Rust calls, not extra MCP requests. Detailed mission events and results are private to the requesting client and are not published in the observatory. ## Typed capability planning and execution - list_composition_capabilities: inspect 14 implemented capabilities (12 engines, one explicit duration adapter, one robust-scheduling composite), 31 versioned fact contracts and reproducible request examples. No proposed SC-2 engine is live. - compose_capabilities: provide goals and available contract IDs, optional allowed tools/locality/search bounds and actual tool argument objects. Rust builds a dependency graph, explains blocked paths and returns an existing-tool binding where available. This is planning only; actual inputs are checked at execution. - execute_composition: recompile and execute the approved optimize_tasks -> selected_durations.v1 -> simulate_plan path. Supply optimize_tasks arguments and simulate_plan {budget, uncertainty, samples, seed}; do not supply durations. The adapter verifies selected identities, totals, integer-minute units and the shared deadline. Real events use the SC_COMPOSITION_EVENT: progress prefix. Structural cost counts graph steps, not measured time, price or scientific quality. Defaults: local_only true, max_steps 8, max_search_states 512, max_structural_cost 64. Bounds: 1-8 goals, up to 48 available contracts, 1-16 steps, 1-2048 expanded states. Missing assumptions or tool permissions are blockers. Search exhaustion does not prove impossibility. Independent goals form a graph, not independent corroboration. The executor accepts 1-32 tasks, a 1-1440 minute shared deadline, uncertainty 0-0.5, and 100-20000 fixed samples. Success means the risk calculation finished, not that the schedule is safe. A 95% Hoeffding interval concerns sampling under the supplied model. Empty selections are blocked. Use build_robust_plan to compare the separate validated family of nominal/10%/20% reserve strategies against a probability target. Only approved execution bindings run. No arbitrary remote URLs or generated code. Documentation: https://scorecompute.com/docs/composition/ ## System availability https://scorecompute.com/status.json provides a sanitized timestamped monitoring snapshot. Discard stale snapshots (90 seconds) and future timestamps (>15 seconds). Status does not reserve a worker or guarantee a calculation will complete. GPU presence comes from worker inventory, not a periodic benchmark. Bounded local service recovery does not resume interrupted jobs or provide distributed failover. ## Interpretation and collaboration Return the model assumptions and limitations with every result. Physical compatibility does not establish image authenticity. A contradiction requires examining inputs and model assumptions. Never label a person fraudulent from these tools. Call optimize_tasks and simulate_plan independently to control each step yourself, or use the optional build_robust_plan tool to compare the bounded candidate family. Only simulate_pi currently implements CUDA. Availability follows the connected compute machine; there is no persistent queue or distributed failover in this alpha. ## Public observatory The website displays declared MCP software client names and tool activity. Client names and versions are self-reported; the AI model's identity is not verified. Do not include secrets or personal data in clientInfo. Tool arguments and results are not published by the observatory. Recent activity is held in memory. ## Documentation - [MCP connection guide](https://scorecompute.com/docs/mcp/) - [Native capability composition](https://scorecompute.com/docs/composition/) - [Engine library](https://scorecompute.com/engines/) - [Monte Carlo simulation with Rust and CUDA](https://scorecompute.com/engines/simulate-pi/): Estimate π with seeded Monte Carlo sampling on CPU or NVIDIA CUDA, with a Wilson confidence interval and reproducible results. - [Exact task selection under a time budget](https://scorecompute.com/engines/optimize-tasks/): Select the highest-value combination of independent tasks under an integer time budget using an exact Rust knapsack solver. - [Schedule uncertainty simulation](https://scorecompute.com/engines/simulate-plan/): Estimate how often a selected task schedule stays within budget by simulating independent duration uncertainty. - [Keplerian orbit calculation for AI agents](https://scorecompute.com/engines/compute-orbit/): Compute an ideal two-body elliptical orbit with a Rust solver for Kepler’s equation, including trajectory and orbital period. - [Solar shadow geometry verification](https://scorecompute.com/engines/verify-shadows/): Compare measured shadow geometry with a calculated solar position using control points, a homography and Monte Carlo uncertainty. - [Sun and Moon position consistency](https://scorecompute.com/engines/check-ephemeris/): Compare a claimed Sun or Moon position with an approximate ephemeris for a UTC timestamp and geographic location. - [GRIM and GRIMMER statistics checks](https://scorecompute.com/engines/audit-statistics/): Screen reported means and standard deviations for arithmetic inconsistency under an integer-valued data model. - [Angular motion and minimum speed](https://scorecompute.com/engines/analyze-kinematics/): Translate an observed angular speed into transverse speed under explicit distance assumptions. - [Temporal shadow consistency in video](https://scorecompute.com/engines/check-shadow-track/): Compare measured shadow directions over time against expected solar motion at a specified place and date. - [Kuhn poker equilibrium with CFR+](https://scorecompute.com/engines/solve-equilibrium/): Explore a small imperfect-information game with a Rust self-play solver and compare its result with a known equilibrium value. - [Chess move comparison with Stockfish](https://scorecompute.com/engines/analyze-chess-game/): Compare supplied chess moves with Stockfish recommendations and inspect an aggregate move-quality profile. - [Trade-pattern consistency screening](https://scorecompute.com/engines/screen-wash-trading/): Inspect supplied trade records for dense round-trip patterns and repeated volume within a price band.