"author:0rkz/byte-mcp-server" matching MCP servers:

Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.

Enables auditing URLs for AI crawler readiness, including 25,000-token RAG truncation, /llms.txt discovery, Lighthouse 13.5 ard-schema compliance, and JSON-LD entities, plus generating manifests and clean Byte-0 Markdown inside MCP clients.

An MCP server that provides access to Semantic Scholar's academic graph, recommendations, and datasets APIs, enabling paper search, citation analysis, author lookups, and dataset discovery through 20+ tools.

Enables MCP clients to persist, search, retrieve, and verify append-only memory records, with every write acknowledged only after append, fsync, byte-exact read-back, and hash-chain validation. It also surfaces truncation and index drift so users can detect silent loss or corruption.

An MCP server that enables verified agents to retrieve from, propose changes to, and share capabilities around a human-owned Markdown/Git knowledge base, ensuring curation, exact-byte approval, and Git-based promotion.

Enables comprehensive academic research through the Semantic Scholar API, including paper search, author discovery, citation network analysis, and full-text access from arXiv and Wiley sources.

Enables AI assistants to search and retrieve stored open-source information through read-only MCP tools, including evidence retrieval by document or snapshot ID with byte-integrity verification.

Enables AI agents to convert PDF, Word, PowerPoint, Excel, HTML, EPUB, Outlook messages and web pages into Markdown for LLM and RAG workflows. Runs over stdio or HTTP and reproduces Microsoft markitdown's output byte for byte without a Python environment.

Enables any MCP client to drive a retrieval-grounded multi-agent workflow over stdio JSON-RPC, with journalled effects so recorded runs replay byte-for-byte from their trace. It also lets an agent answer retrieval by calling a tool on another MCP server.

A comprehensive Model Context Protocol server that provides AI assistants with direct access to Semantic Scholar's academic database, enabling advanced paper discovery, citation analysis, author research, and AI-powered recommendations.

Enables semantic search and ingestion of investor content using Upstash Vector and Vercel Blob storage, with optional filtering by author, company, and date.

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.

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Gives any MCP client 27 tools for turning scattered feeds, forums, and media into a persistent, searchable evidence corpus, so an agent can search and import evidence, verify claims with independent-source counting and citation checks, and run multi-round research that produces cited, revisable reports. It also supports adaptive retrieval widening, tiered evidence where only author-written sections count as sources, and honest degradation when no LLM key is available.

Enables hybrid retrieval-augmented generation with semantic and keyword search over documents, supporting multiple formats and providing MCP integration for Claude Desktop.

Enables semantic and keyword search across locally indexed PDF shelves—device manuals, meeting minutes, and scientific papers—with date, device, and author filters, returning structured citations and neighbouring passage context for a speech assistant. It also exposes shelf and document metadata, plus a reindex signal, over streamable HTTP backed by Postgres with pgvector.

A local MCP server that lets agents search shared skills hosted in public or private git repos, showing ranked matches with author and dates, and load a chosen one only for the current session. It indexes those repos locally, so local skills stay untouched and shared skills are fetched on demand.

A pluggable, observable modular RAG service framework that exposes tool interfaces via the MCP protocol, enabling AI assistants like Copilot and Claude to directly query knowledge bases.

A local knowledge base MCP server that enables retrieval and evidence-based Q&A over Obsidian Markdown notes, with high-recall embedding search, chunked indexing, hybrid retrieval, and three STDIO MCP tools for agent-driven recollection and quality-gated recall.

Enables agents to search a document collection by query, fetch a complete document by its ID, and generate bounded summaries of supplied text, with Pydantic-validated tool inputs.