"author:Alpha-Park" matching MCP servers:

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables autonomous web agents to prune DOM trees, canonicalize URLs, auto-map form inputs, and convert HTML/Markdown tables into typed JSON, then score execution trajectories with action-level precision, recall, and Levenshtein edit distance against gold benchmarks. Runs as a zero-dependency, stdlib-only MCP server over JSON-RPC 2.0 stdio for Claude Desktop, Cursor, and Windsurf.

Enables autonomous web form inspection and schema auto-mapping by matching input attributes, autocomplete hints, and regex validations to agent state, while also pruning DOMs and converting tables into structured JSON for web agents.

Enables autonomous web agents to prune raw HTML into accessibility-friendly semantic trees with 80%+ token reduction, auto-map form input schemas, convert HTML/Markdown tables into type-inferred JSON records, and score agent execution trajectories. Runs as a zero-dependency, stdlib-only MCP stdio server for Claude Desktop, Cursor, and Windsurf.

Enables autonomous web agents to canonicalize URLs, detect anti-crawler traps such as circular paths and infinite pagination, prune DOM tokens, auto-map forms, transform tables into JSON, and evaluate action trajectories through MCP.

Enables AI agents to anchor visible on-screen elements to stable DOM targets, preventing click drift during browser computer-use automation.

Enables AI agents and MCP-compatible clients to analyze web checkout form fields and heuristically resolve and autofill buyer parameters through a deterministic, zero-dependency engine. Plugs into Claude Desktop, Cursor, or Windsurf over JSON-RPC to return structured autofill results and execution telemetry.

Enables autonomous web automation by flattening DOM trees into pruned accessibility trees, synthesizing robust CSS/XPath locators, and compiling goal-driven multi-step action plans with verification. It exposes these capabilities through MCP JSON-RPC tools for browser-oriented task execution.

Enables autonomous browser action planning by mapping goals into resilient selector action sequences, with deterministic execution and structured telemetry through MCP.

Enables AI agents and MCP clients to fetch web pages and distill them into clean, token-efficient markdown by stripping cookie banners, navigation bars, and ads. Runs with zero external dependencies over JSON-RPC stdio, delivering deterministic sub-millisecond results without LLM round-trips.