MCP servers

Enables AI agents to synthesize and update hierarchical episodic and semantic user profile memory graphs through MCP, using deterministic zero-dependency Python processing with JSON Schema validation.

Official·1 source

Extracts and structures executive meeting action items and decision accountability into JSON, enabling automated tracking and telemetry through MCP-compatible AI agents.

Official·1 source

genpark-fintech-transaction-velocity-fraud-sentinel-skill

Enables autonomous financial agents and payment systems to analyze transaction streams in real time, detect velocity-based fraud patterns such as card testing, volume spikes, and account takeovers, and produce balanced ledger records with audit telemetry.

Official·1 source

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.

Official·1 source

Generates fullstack UI component AST patches with Tailwind tokens, enabling AI agents to produce structured UI patch outputs for frameworks like v0 and Lovable.

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Enables agents to compute shortest paths with Dijkstra and A*, resolve DAG dependencies, solve maximum flow, build minimum spanning trees, and rank graph centrality using JSON-RPC MCP tools.

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genpark-graph-dijkstra-astar-pathfinder-skill

Enables graph pathfinding and network analysis through MCP, including Dijkstra/A* shortest paths, topological dependency resolution, maximum flow, minimum spanning trees, and PageRank centrality for agent planning.

Official·1 source

It enables autonomous browsing clients to canonically compress rendered HTML into compact semantic trees, filter navigation traps, bind webform schemas, transform tables into typed records, and score interaction trajectories. Its tools operate locally over stdio with no runtime third-party requirements.

Official·1 source

genpark-hubx-ai-apps-orchestration-skill

Enables agents to orchestrate and call tools across HubX's mobile AI app portfolio for multi-model chat, plant/vision diagnostics, generative image and design, nutrition tracking, audio note summarization, language tutoring, and wellness workflows through a unified MCP interface with structured JSON output.

Official·1 source

Enables autonomous agents to orchestrate HubX mobile AI tools for vision diagnostics, voice transcription, photorealistic image generation, and spatial design through a native MCP interface.

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Enables deterministic reconstruction of complex tables from OCR bounding-box payloads, recovering multi-column layouts, merged headers, and grid hierarchies. It also supports formula consistency auditing and sensitive PII redaction for document processing pipelines.

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Enables fusing and reranking results from multiple search or retrieval sources using Reciprocal Rank Fusion and hybrid rank fusion. It provides deterministic scoring, robust parsing, and structured JSON output for autonomous agent workflows.

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genpark-hypothesis-welch-t-test-statistical-evaluator-skill

Enables statistical A/B testing by computing Welch's two-sample t-test, Satterthwaite degrees of freedom, and two-tailed p-values, alongside time-series forecasting, anomaly detection, regression, and PCA through MCP tools.

Official·1 source

Enables MCP clients such as Claude Desktop, Cursor, and Windsurf to run two-sample Welch's t-tests that compute Satterthwaite degrees of freedom and two-tailed p-values for A/B test comparisons. It also exposes zero-dependency statistical primitives including Holt linear forecasting, Z-score/IQR anomaly detection, gradient-descent regression, and power-iteration PCA, all using only the Python standard library.

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Enables autonomous financial agents and payment webhooks to create and verify immutable double-entry ledger entries, enforce debit-credit balance invariants, and generate hash-chained audit trails with fraud detection.

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Enables auditing influencer brand safety and multi-year controversy history through Traackr.

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Enables monitoring influencer brand share of voice and creator mention sentiment using Meltwater data, delivering deterministic structured output for MCP-compatible clients.

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Enables personal AI agents to sense ambient attention cues, compute intent probabilities, and execute reversible guarded dry-run actions without prompting. It routes routine reflexes through a fast System-1 decision layer backed by decaying episodic memory and strict safety and privacy guardrails.

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Enables zero-dependency INT8 symmetric quantization of LLM weights and activations on a per-tensor or per-channel basis, reporting SNR and MSE reconstruction telemetry along with TTFT/TPOT latency and jitter metrics. Also exposes edge inference primitives such as PagedAttention block allocation, radix prefix caching, and speculative decoding verification through the Model Context Protocol.

Official·1 source

Enables AI agents to resolve typed routing, loop-stall arbitration, and tool safety checks locally at sub-millisecond latency, avoiding unnecessary frontier LLM calls. It enforces reversible execution checkpoints, token budgets, and decayed episodic memory for safe, privacy-first autonomous operation.

Official·1 source

Enables MCP-compatible agents to arbitrate typed state-action schemas, dispatch routine actions deterministically, and apply pre-escalation filters that reduce unnecessary frontier LLM calls. It supports low-latency, schema-enforced routing with safety guardrails and local-first memory retention.

Official·1 source

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Official·1 source

Enables agents to cryptographically verify JWT HMAC-SHA256 signatures, validate claims and enforce expiration, and perform Merkle inclusion proofs, Schnorr zero-knowledge identification, and nonce replay protection. Runs as a zero-dependency stdio MCP server so clients like Claude Desktop, Cursor, and Windsurf can attest execution state without OpenSSL or external libraries.

Official·1 source

genpark-jwt-hmac-sha256-token-attestation-skill

Enables agents to cryptographically attest and verify identity and execution state through RFC 7519 JWT HMAC-SHA256 signature checks, claims and expiration validation, constant-time secret comparison, SHA-256 Merkle inclusion proofs, Schnorr zero-knowledge identification, and sliding-window nonce replay protection. It runs as a zero-dependency Python MCP server over stdio, so it can be attached to Claude Desktop, Cursor, or Windsurf without external libraries.

Official·1 source