"author:alphaparkinc" matching MCP servers:

Enables agents to ingest payment webhooks and ledger transactions with cryptographic HMAC-SHA256 signature verification, sliding-window replay tolerance, and atomic idempotency locking. It also enforces double-entry debit/credit invariants and returns balanced journal records with audit and risk telemetry over MCP.

Enables users to compute European option prices and sensitivity metrics, run Monte Carlo GBM simulations, calculate historical/parametric VaR/CVaR, evaluate bond duration and convexity, and interpolate Nelson-Siegel yield curves through MCP.

Enables long-horizon autonomous task checkpointing and resumption through cryptographic event-sourced state persistence, idempotency key deduplication, timeout heartbeats, human-in-the-loop pause/resume tokens, and fail-safe recovery.

Enables users to simulate quantum circuits, evolve qubit state vectors, apply gates such as Hadamard and CNOT, perform Born-rule projective measurements with Monte Carlo shot histograms, and run Grover amplitude amplification through MCP-compatible clients.

Enables MCP-compatible agents to execute bash and subprocess commands through a zero-dependency sandbox guard that blocks destructive system mutations, path traversals, reverse shells, and other unsafe execution patterns.

Enables AI agents to coordinate atomic distributed transactions across a swarm through a prepare/vote phase, unanimous commit-or-abort consensus, quorum validation, and failure recovery. It also layers in vector-clock causal stamping, LWW CRDT reconciliation, and gossip dissemination so multi-node state converges deterministically without external dependencies.

Enables autonomous agents to detect under-specified user goals, gauge reversibility and risk, and present minimal multiple-choice clarifications before committing to high-stakes execution.

Enables agents to perform Schnorr zero-knowledge identification and cryptographic attestation through a native MCP interface, including commitment-challenge-response proofs, JWT validation, Merkle inclusion checks, and replay protection.

Enables running second-price Vickrey auctions that match consumer query intent with brand bids while preserving organic recommendation neutrality. It integrates as a zero-dependency MCP server for agentic commerce and privacy-preserving ad monetization workflows.

Enables MCP clients to run bounded epidemic dissemination, causal ordering, conflict-free state merging, and quorum-based transaction coordination across autonomous agent swarms.

Enables AI agents to run structured multi-persona debates over high-stakes decisions and merge their positions into an explainable consensus, complete with logged dissenting minority opinions. It runs as a zero-dependency Python MCP server or importable module, compatible with Claude Desktop, Cursor, and custom agent frameworks.

Enables autonomous agents to detect configuration drift, corrupted execution state, and missing runtime resources, then perform root-cause classification and automated snapshot rollback for self-healing runtime recovery.

Provides native MCP tools for quantitative-finance and risk-modeling workflows, enabling computation of option Greeks, simulation of geometric Brownian motion asset-price paths, historical/parametric VaR and CVaR estimates, bond duration/convexity metrics, and Nelson-Siegel yield-curve interpolation using only Python's standard library.

Enables agents to synthesize multi-tab enterprise spreadsheet financial models, detect circular references, compile formula dependency DAGs with functions like SUMIFS/XLOOKUP/CAGR/NPV, and evaluate deterministic preview cell matrices.

Enables MCP clients to guard agent API requests against nonce replay attacks using a sliding-window ledger, constant-time digest checks, JWT claim validation, Merkle inclusion proofs, and Schnorr zero-knowledge verification.

Enables clients to optimize prompt prefix caching by matching longest common token prefixes with a radix trie, eliminating redundant prefill computation and reducing time-to-first-token.

Enables agents to track causal relationships, reconcile concurrent state changes, and coordinate consensus across distributed networks using vector clocks, CRDTs, gossip, and quorum-based protocols.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Enables personal AI agents to perceive ambient context, retain episodic memory with decay, act proactively, and route routine decisions through fast System-1 reflexes while escalating ambiguous multi-hop plans to frontier LLMs. Includes reversible execution checkpoints, token budgets, and local-first memory retention, and plugs into MCP clients like Claude Desktop, Cursor, and Windsurf.

Enables real-time multi-merchant price comparison, coupon stacking, delivery-speed trade-offs, stock volatility tracking, and optimal purchase routing for cross-platform commerce inventory arbitrage.