"author:666666999999666" matching MCP servers:

Give MCP-compatible AI agents image analysis, metadata inspection, cropping, OCR, and image comparison through any OpenAI-compatible vision model.

Persistent AI memory for Claude Code, Cursor, GitHub Copilot & Windsurf — sessions, lessons learned, semantic search, and team brain. 38 MCP tools. Free tier, EU servers.

AI-powered academic paper search MCP server with relevance scoring, summarization, author search, and credit checking. Enables users to search papers naturally and get scored results.

Hosted MCP server for structured knowledge extraction and entity enrichment, allowing users to author JSON schemas, enrich entities using multiple LLM providers, and benchmark model performance.

Author verifiable eval records through a draft → review → revise → submit loop with server-enforced graders; compile to JSONL/CSV/Inspect/lm-eval via MCP.

Buying-intent judgement for AI agents: three judges decide whether the author of any post or message is a real buyer, and draft a reply you approve.

Provides structured visual analysis tools for coding agents, enabling UI analysis, screenshot comparison, OCR, and crop-based refinement through VLM.

Enables admins to author and manage persistent mock MCP servers and OpenAI-compatible endpoints through a browser UI and admin API, with REST mocks, shared datasets, and traffic logging for demos and training.

Resolves what an MCP tool call would do by planning it: it merges inputs, substitutes static placeholders or asks a model to author commands and queries, checks them against guardrails, and returns the masked plan with targets plus a dispatch verdict. It executes nothing and connects to no database, gateway, or queue, so it can run anywhere and be tested without infrastructure.