An MCP server implementing Recursive Language Models (RLM) to process arbitrarily large contexts through a programmatic probe, recurse, and synthesize loop. It enables LLMs to perform multi-step investigations and evidence-backed extraction across massive file sets without being limited by standard context windows.
An MCP server implementing the TRUE Recursive Language Model technique for managing large context windows in Claude Code, enabling analysis of codebases beyond 200k tokens by storing content as variables and using LLM-generated code for search and analysis.
MCP server that lets Claude analyze huge files (logs, dumps, etc.) via a sandboxed Python REPL and recursive language models, keeping content out of the prompt. Zero-setup with Claude Code login, Docker sandbox by default, and tools for loading, searching, chunking, and querying large contexts.
A local MCP server that ingests entire repositories into a large context window (GLM-5.2 1M tokens) for coding agents, bypassing file limits and reducing query costs.
MCP server that enables AI to read, search, and edit local files securely without external data exposure, using local LLMs via Ollama and integrating with Open WebUI or Claude Desktop.
