Reducto

Reducto MCP Server connects AI agents to Reducto's document-processing APIs through the Model Context Protocol. MCP clients such as Claude Desktop, Claude Code, Codex, Cursor, VS Code, and Windsurf can use it to upload, classify, parse, extract, split, and edit documents, chaining those operations in an agent reasoning loop without custom integration code. It is available as a hosted HTTP server at mcp.reducto.ai/mcp or as a local server run with uvx. The hosted option accepts public URLs, while the local option can read local file paths and public URLs and uses Reducto credentials. The server is described in the accompanying talk as an agent-oriented interface with tools that represent document pipeline work, a snapshot of live pipeline state, confidence scores, and an ask-user mechanism intended to avoid silent guesses.

RE:Dox is an open-source, Apache-2.0-licensed structured-data engine for .NET, developed by CAPCOM as a core component of its REX technology. It parses JSON and other supported formats into a compact token DOM/intermediate representation in which fixed-size tokens can retain source offsets, lengths, links, or inline values; this representation supports reading, editing, serialization, deserialization, and format conversion. The mutable token model provides node-like insert, remove, and replace operations without rebuilding a managed object tree, while lazy decoding can defer materializing strings, numbers, timestamps, and binary values. Its asymmetric I/O design writes known values directly through a DataWriter, while deserialization first builds an addressable token DOM for look-ahead, out-of-order constructor binding, reference resolution, and optional automatic parallel processing of large arrays. The core packages support JSON, JSON5, CBOR, MessagePack, INI, and the binary DOX format, with TOML, XML, HTML, and CSV integrations listed as preview components. A common DataReader/DataWriter and DataConverter model enables conversion between formats such as JSON, CBOR, MessagePack, TOML, XML, and DOX, subject to structural projection where formats have different data models. JSON5 editing can preserve comments and other trivia, and JsonSequence supports asynchronous processing of NDJSON or large top-level JSON arrays without loading the entire input. Compatibility packages are provided for System.Text.Json, Newtonsoft.Json, and DataContractJsonSerializer. The project requires .NET 10 or later, is distributed through CAPCOM.REDox.* NuGet packages, and is under active development; its README notes that APIs, package boundaries, and preview-format support may change before the first stable public release.

doc7 is an open-source document-to-Markdown tool that converts PDFs, Office files, scans, screenshots, charts, formulas, and diagrams into AI-ready Markdown using an OpenAI-compatible multimodal vision model. It renders and understands complete pages rather than relying on character extraction, preserving text, tables, formulas, chart and diagram relationships, image meaning, and visible UI state; the video also describes page-level retry and resume. The model can run locally through LM Studio or Ollama or through a remote endpoint, with no required OCR stack or document-processing service. The same binary provides an interactive CLI, batch processing, model checks, MCP support, a Go SDK, and an asynchronous HTTP service, with installers for macOS, Linux, and Windows.

Ratel is an in-process context-engineering platform for AI agents. It catalogs tools, skills, and persistent facts, then searches the catalog on each turn and progressively discloses only the capabilities relevant to the request instead of placing every tool schema and instruction in the context window. Its retrieval supports BM25, semantic, and hybrid ranking without requiring a vector database. The project includes a Rust core, TypeScript and Python SDKs, an MCP server, and a CLI. Tools can be registered directly or ingested from an MCP server; skills can associate instructions with tools, while registered facts are re-injected when they are no longer fresh in the conversation. The repository describes the system as reducing token usage and mitigating tool overload.

anydoc is an open-source Rust library from Firecrawl that converts Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV, and PDF files into GitHub-Flavored Markdown. It uses a shared document model and provides Node.js, Python, browser WebAssembly, and Rust interfaces, along with a command-line interface that reads files or standard input and writes Markdown to standard output or a file. The library can return either Markdown or its intermediate document model, which carries embedded assets. A browser demo runs the WebAssembly build locally, while hosted OCR through Firecrawl Parse can process scanned PDF pages that anydoc cannot read by itself. It is also distributed as an agent skill compatible with agent tools such as Claude Code, Codex, Cursor, and OpenCode.