"author:alphaparkinc" matching MCP servers:

Enables users to transform raw multi-source enterprise findings into complete, structured strategic documents, auto-generating executive summaries, risk registers, decision matrices, and appendix citations. It runs as a zero-dependency Python MCP server that works with Claude Desktop, Cursor, and other MCP-compatible clients.

Enables AI agents and developers to dynamically tokenize session context windows and compact dialogue history into structured outputs via MCP, CLI, or Python client. Runs on pure standard library Python with no external dependencies for deterministic, low-latency execution.

Enables transforming raw enterprise documents, meeting transcripts, and KPI metrics into structured executive slide decks with layout templates, card callouts, speaker notes, and timing budgets. Integrates through MCP to support deterministic, zero-dependency slide narrative compilation.

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.