— · AGPL-3.0
LLM-Driven Extraction of Unstructured Data — Built for API Deployments & ETL Pipeline Workflows
v2.0.0 · Apache-2.0
Turn local files into searchable context for AI agents.
v0.1.0 · MIT
在 DeepSeek Harness / Claude Code / Cursor / Codex / Gemini CLI 里直接搜索 20 个中国开放平台的 65,600+ 篇 API 文档;零配置,支持 Skill 与 DSH 原生插件。
v3.0.1 · MIT
Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.
v1.24.11 · no license
TapTap 小游戏开放能力 mcp
v2.0.0 · MIT
Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors
v0.18.0 · SEE LICENSE IN LICENSE
Enterprise-grade, local-first Agent Workbench for people and agent teams. A unified multi-engine workspace for Codex Harness, DeepSeek Harness, and OpenCode, with unified plugins and Skills, multi-agent projects and tasks, and editable code, documents, presentations, design, and video.
v0.14.5 · Proprietary
ClickUp MCP Server - Powering AI Agents with full ClickUp task, document, and chat management capabilities.
v0.1.0 · AGPL-3.0-only
Your AI agent, fluent in Australian tax. MCP server with cited answers from 34,500+ ATO documents, the income tax and GST Acts and 4,900+ rulings, plus deduction, depreciation, BAS and audit-risk tools that know your tax profile.
— · no license
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
v4.1.8 · AGPL-3.0-or-later
Local-first agent memory with MCP and an agent-native CLI. Documented clients include Claude Code, Cursor, and Windsurf.
— · Apache-2.0
Open Source Implementation of Karpathy's LLM Wiki. Upload documents, connect your Claude account via MCP, and have it write your wiki !
v1.6.8 · MIT
Local-first memory, hybrid RAG, and agent personalization for AI coding agents (OpenCode, Claude Code, Codex, Gemini CLI, Antigravity). MCP server + CLI with persistent context, document ingestion, vector + SQLite FTS5 retrieval, sync, setup, and safe uni
— · MIT
CTX: a tool that solves the context management gap when working with LLMs like ChatGPT or Claude. It helps developers organize and automatically collect information from their codebase into structured documents that can be easily shared with AI assistants.