Search, chat, upload, and scrape a serverless RAGStack knowledge base on AWS.
Production-ready RAG platform combining graph, vector, full-text, and vision search with AI agents and MCP integration.
Key Features: Five index types: vector, full-text, graph, summary, vision Built-in AI agents with MCP tool support Advanced entity normalization for cleaner knowledge graphs Zero-trust, air-gapped Enterprise GraphRAG MCP server with offline, citation-grounded answers.
Searches private local Markdown, PDF, and Tika-backed content through a read-only MCP interface on Windows.
Key Features: Local Markdown and PDF search Tika-backed document indexing MCP server providing secure, authenticated access to Vectara's RAG platform via HTTP, SSE, or STDIO transports.
Key Features: Supports HTTP, SSE, and STDIO transport modes Built-in bearer token authentication with optional disabling for dev Rate limiting and CORS origin validation for HTTP transport Builds local searchable indexes for documents and supports agent-filtered RAG with provenance and source citations.
Key Features: PDF, EPUB, DOCX, and Markdown parsing Deterministic chunking with YAML front matter SHA-1, SHA-256, and BLAKE3 provenance hashes MCP server for managing CustomGPT.ai agents, conversations, content sources, settings, statistics, and API documentation.
Key Features: Agent listing, creation, settings, and statistics Conversation and message-history access Page, sitemap, and uploaded-file management Adds local RAG chat, an HTTP server, and an embeddable widget to websites using markdown content and an LLM API key.
Key Features: Markdown section-based knowledge-base setup Local JSON vector store with cosine similarity search OpenAI, Anthropic, Gemini, and AWS Bedrock provider support Provides repository-aware documentation context, convention checks, API context, and proposed documentation updates through MCP.
Key Features: Repository-aware AI context Convention discovery with citations Documentation impact analysis Connects Scrivener 3 projects to AI clients for editing, analysis, search, and writing support.
Key Features: Scrivener 3 document access and editing Deterministic writing analysis Keyword and offline semantic search Searches, inspects, submits, verifies, and manages MCP server listings through agent tools or a scriptable CLI.
Key Features: Directory search by keyword and category Installation configuration lookup Read, search, and manipulate Git repositories through MCP using a local Python package.
Key Features: Manipulate local repositories