A multi-agent research system that decomposes complex queries into targeted sub-questions, searches the web in parallel, scores source credibility, and synthesizes findings into structured markdown reports.
A memory system for AI agents that maintains a human-readable, typed Markdown knowledge base with an always-in-context index, enabling recall, correction, and trust decay through MCP.
Simulate hundreds of AI agents to predict how communities react to events and policies. Upload any document (PDF, Markdown, text) and DeepMiro spawns a diverse swarm of AI agents that debate, share, and form opinions — then delivers a calibrated prediction report. Free and open-source.
Provides a hybrid memory architecture with a thin SQLite index and Markdown cold storage, enabling AI agents to write, query, link, and rebuild long-term memories via MCP tools, model-agnostic and zero third-party dependencies.
Enables the creation and execution of task-specific AI sub-agents defined in markdown across any MCP-compatible tool like Cursor or Claude Desktop. It integrates with execution engines such as Claude Code, Cursor CLI, and Gemini CLI to provide portable and reusable specialized agent workflows.
Enables AI agents to manage hierarchical memory with Markdown-based storage, tiered architecture (L0-L3), and hybrid retrieval for transparent and persistent context.
A context preservation engine for AI agents that bundles project state into a markdown package and syncs it to clipboard or cloud, enabling zero knowledge loss across sessions.
Agent Toolbelt is an MCP server exposing 11 focused API tools for LLM agents — schema generation, text extraction, token counting, CSV conversion, Markdown conversion, URL metadata, regex builder, cron expressions, address normalization, color palettes, and brand kits. Each tool is a focused microservice with structured input/output, WCAG-scored color data, USPS address parsing, and multi-model to
A Model Context Protocol server that converts Markdown content into interactive mindmaps, allowing AI assistants to visualize hierarchical information through either HTML content or saved files.
TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.
Automatically generates structured agile backlogs including epics, features, and user stories from natural language descriptions within AI-powered IDEs. It streamlines project management by creating AI-optimized markdown files and directory structures to guide step-by-step implementation.
Persistent memory for AI agents built on the LLM Wiki pattern: a plain-Markdown brain (also a valid Obsidian vault) with SQLite metadata, local semantic search via fastembed (no API keys), one-call session context with project auto-detection, and a decision log with rationale. Works with Claude Code, Claude Desktop, Cursor, and any MCP client.
A persistent memory server for AI agents that stores findings, tasks, and patterns in Markdown files within a git repository, enabling context injection across multiple AI tools.
End-to-end agent-managed company brain. Humans and any MCP agent co-author living docs (Markdown + extensions), 40+ visual diagrams (Mermaid, BPMN, D2, PlantUML, ELK, Excalidraw), plans, and a self-learning Knowledge Graph. 163 tools across 16 categories. Auth: OAuth 2.1 or API key. Lean, secure, affordable — from individuals to enterprise.
Enables AI agents to create, manage, and track tasks within plans using Valkey as the persistence layer. Supports plan and task management with Markdown notes, status tracking, and prioritization through multiple transport protocols (SSE, Streamable HTTP, STDIO).