"author:alphaparkinc" matching MCP servers:

Enables extraction of subject-predicate-object triples from text and multi-hop reasoning over connected data, producing Cypher and JSON-LD outputs for agent memory, vector search, and retrieval-augmented generation workflows.

Enables cryptographic chunk hashing, reverse claim-to-source attribution, clearance boundary validation, and provenance audit trails for enterprise knowledge graphs to combat hallucinations.

Enables agents to maintain multi-tier memory across working scratchpad, dialogue buffer, and episodic stores with recency decay. Supports hybrid BM25/vector retrieval, rank fusion, graph expansion, and context reordering for optimized MCP-based memory and RAG workflows.

Enables agents to optimize context-window attention by reordering retrieved documents so critical evidence lands at prompt boundaries, mitigating lost-in-the-middle degradation. It combines BM25 lexical scoring, dense vector similarity, reciprocal rank fusion, knowledge-graph expansion, and recency-decay memory caching, exposed as a zero-dependency MCP stdio server.

Enables inspection and governance of enterprise ingested context by classifying security clearance tiers, sanitizing cross-department prompts, and enforcing role-based access boundaries to prevent data leaks. It runs as a zero-dependency MCP server compatible with Claude Desktop, Cursor, and other agent frameworks.

Enables high-throughput semantic query caching and approximate deduplication by combining exact SHA-256 matching, cosine similarity threshold checks, and LRU eviction.

Enables hybrid retrieval over agent memory and documents by fusing BM25 lexical and cosine vector rankings with reciprocal rank fusion, plus knowledge graph expansion, semantic caching, and context reordering for RAG.

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.

Enables long-horizon conversational memory compaction and episodic anchor extraction for AI agents, providing deterministic memory management through a zero-dependency MCP server.

Enables deep research evidence synthesis and citation verification by generating structured research graphs through the Model Context Protocol.

Enables decomposition of complex research queries into multi-hop sub-queries and synthesis DAGs, with scientific consensus analysis, citation credibility verification, and deterministic JSON outputs for MCP-compliant clients.

GenPark MCP server for selecting relevant context under token and latency constraints.

Enables deterministic auditing of RAG retrieval faithfulness and hallucination scores, providing structured JSON output for AI agents and MCP-compliant clients.

Enables AI agents and MCP clients to dynamically select few-shot in-context examples using semantic token overlap, cosine similarity, and MMR diversity ranking to optimize prompts deterministically without external dependencies.

Enables sentence-level factual grounding verification and hallucination detection for RAG outputs via MCP, with deterministic scoring and structured telemetry.

Enables autonomous agents and MCP clients to decompose text into atomic claims and verify them against reference knowledge, detecting ungrounded claims, numerical contradictions, and hallucinated entities.

Enables AI agents and MCP clients to compress retrieved web documents against a query, pruning irrelevant noise through deterministic algorithmic scoring so downstream context stays lean. It exposes this capability over the Model Context Protocol for integration with Claude Desktop, Cursor, and similar clients.

Enables deterministic hybrid ranking by fusing dense, sparse, and BM25 retrieval results with reranking and Reciprocal Rank Fusion, producing structured output via MCP for AI agents.

Enables AI agents and MCP-compatible clients to perform hybrid episodic long-term memory retrieval by combining BM25 keyword search, semantic n-gram cosine similarity, and recency decay ranking over stored memories.