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Software like llmwiki
What else does this job. Matched on what each project does, not on who links to whom.
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- LLM Wikillm-wiki.netLLM Wiki is a knowledge base tool for AI agents. It compiles topic wikis from source material and supports parallel multi-agent research, thesis-driven investigation, source ingestion, wiki compilation, session memory, feedback curation, topic archiving, inventory tracking, dataset manifests, truth-seeking audits, token-efficient read-only querying, and artifact generation. Its workflow is built around turning raw sources into cross-referenced articles and then into outputs such as reports, slide decks, study guides, playbooks, implementation plans, timelines, glossaries, and comparisons. The tool can dispatch up to ten agents, search academic, technical, applied, news, and contrarian angles, and run a thesis mode that splits agents across supporting, opposing, mechanistic, meta, and adjacent perspectives to produce a verdict rather than a summary. It also ingests URLs, files, PDFs, inbox drops, Git doc repos, MediaWiki dumps, message archives, and Wayback CDX snapshots. Raw sources remain immutable while articles are synthesized on top, and the system can dedupe, catalog artifacts, track durable follow-up state, index large external data with manifests and profiles, and maintain human-owned schema.md topic guides. LLM Wiki ships as a Claude Code plugin, an OpenAI Codex plugin, an OpenCode instruction file, or a portable AGENTS.md. It is Obsidian-compatible. The documentation also describes a full workflow and a read-only querying path, with compact file-cited lookup available through wiki-query. Sessions are captured under .sessions/ with redacted events, state JSON, and Markdown digests, and feedback, librarian scoring, audit, lessons, and plan-generation functions are described as part of the same system. The page refers to it as llm-wiki by nvk. No pricing or license terms are stated in the provided material.
- LLM Wikillmwiki.appLLM Wiki is a free, open-source tool designed to compile and maintain a structured wiki from raw documents using large language models. It addresses the challenge of synthesizing and organizing research, particularly on transformer architectures and their scaling properties, by automating the creation and upkeep of a knowledge base. The platform is an open-source implementation inspired by Karpathy's LLM Wiki. The tool operates by ingesting sources such as articles, papers, notes, and transcripts, which serve as the immutable foundation for the wiki. Upon adding a new source, the LLM reads the content, writes a summary, updates relevant entity and concept pages, and flags any contradictions with existing information. This process can affect multiple wiki pages per source, allowing for comprehensive updates and cross-referencing. The generated wiki consists of markdown pages that include summaries, dedicated entity pages, and extensive cross-references, all authored by the LLM. Users interact primarily by reading the wiki and posing complex queries against the synthesized knowledge, rather than re-deriving answers from raw data each time. Notably, valuable answers from these queries are incorporated back into the wiki as new pages, enabling the knowledge base to grow and refine over time. LLM Wiki also offers linting features that run health checks across the wiki to identify inconsistencies, outdated information, orphaned pages, and missing cross-references. The LLM can suggest new questions to explore and recommend additional sources to ingest, further enhancing the depth and accuracy of the knowledge base. The schema layer, defined by a configuration file, determines the structure of the wiki, the conventions to be followed, and the workflows to be executed during ingestion. 0 license, and its open-source nature allows users to access, modify, and deploy the tool as needed. LLM Wiki is suited for those seeking to automate the organization and synthesis of complex research materials, leveraging LLMs to handle the often tedious aspects of knowledge base maintenance.
- llmwiki-servepypi.orgllmwiki-serve is a Python package that turns existing Markdown, Obsidian-style, or LLMWiki folders into clean, cited, agent-readable context. It is designed for retrieval-augmented generation (RAG) and autonomous AI agents, supporting the Model Context Protocol (MCP). The tool is open source under Apache-2.0 and helps bridge personal knowledge bases with LLM workflows.
- llm-wikibasepypi.orgllm-wikibase is an open-source CLI tool that uses large language models to synthesize and organize knowledge into markdown-based knowledge bases at the time of data ingestion. It is designed for technical writers and documentation teams.
- wiki-compilerpypi.orgwiki-compiler is an open-source CLI tool that compiles documents, papers, and notes into an Obsidian-compatible markdown wiki. It automatically generates wiki-links and backlinks, streamlining the process of building a personal knowledge base for users who prefer markdown and Obsidian.
- llm-wiki-agentgithub.comllm-wiki-agent is an open-source Python package that provides initialization and platform adaptation for LLM Wiki agents. It supports cross-platform usage and integrates with the Model Context Protocol (MCP), targeting AI developers and researchers.
- llm-wiki-mcppypi.orgllm-wiki-mcp is an open-source MCP server and Claude Code skills package for creating persistent markdown knowledge bases with LLMs. It enables agents to grow and manage wikis over time, supporting developers building LLM-powered documentation and knowledge systems.
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