"Information about Automata Labs Team" matching MCP servers:

Enables AI agents to join one shared room over MCP where they message each other, post live status, read and write shared notes, and use shared connections such as Zapier, all from a single self-hosted process. Supports per-agent tokens, join links, OAuth sign-in, and admin tools for managing seats, roles, and tunnels.

Provides coding agents read-only access to the Neat Labs component and style library, enabling them to search and retrieve components, styles, themes, token roles, and preview links.

Read, search, and write Obsidian vault notes via Team Relay collaborative server. Supports shared folders, real-time sync, and AI agent access.

MCP server for bottle-cap CAD workflow, providing tools for generating precise caps, filling holes, repairing meshes, and generating visual meshes via CadQuery, PyMeshLab, and the Meshy API.

Enables orchestrating a reusable team of expert agents (PM, architecture, development, QA, security) to analyze a project's files and produce consolidated recommendations. It exposes tools to list experts, ask a single expert, or run the full team from MCP clients.

Enables users to leverage a team of specialized AI agent personas like Business Analysts and Product Managers through a unified interface across multiple LLM providers. It streamlines agile development workflows by providing tools for model discovery, unified prompt delivery, and role-specific decision making.

Shared team memory for AI coding agents with Bayesian confidence scoring and temporal decay, enabling persistent storage and retrieval of engineering patterns across sessions.

A Model Context Protocol Server that enables language models to access and manipulate Readwise documents and highlights programmatically.

Enables structured robustness and security testing by scanning text for policy/safety issues and generating test suite outlines.

An MCP server to create secure code sandbox environment for executing code within Docker containers.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Contract-driven test enforcement and reporting for LLM-generated code via MCP, VS Code, Copilot CLI, Claude, Cursor, or Python SDK.

Enables AI coding assistants to query and store a team's historical development experience through semantic search, so lessons and decisions persist across conversations.

A reusable AI software development team built on MCP. 13 specialized agents (Project Manager, Backend, Frontend, QA, Security, DevOps, UX, and more) collaborate via shared SQLite state. Exposes 44 MCP tools across 12 domains. All discussions and decisions are stored in the database so agents get back up to speed immediately when re-loaded.

Provides team information retrieval capabilities through HTTP streaming transport. Built with FastMCP 2.0+ and includes ngrok integration for easy testing and development.

Durable memory MCP server for AI agents. Temporal knowledge graph with hybrid semantic + keyword retrieval, LLM-powered fact extraction, conflict detection, and consolidation. Backed by SQLite or PostgreSQL. 11 MCP tools, 6 LLM provider backends. Part of JamJet.

Two MCP endpoints for building cognitive AI agents. /blueprint/mcp serves a 9-chapter architecture blueprint (4 tools). /devops/mcp serves a 7-chapter coding agent playbook (3 tools). Each product has its own Gumroad license key. Free chapters available without auth.

An MCP server that implements Retrieval-Augmented Generation to efficiently retrieve and process important information from various sources, providing accurate and contextually relevant responses.

Enables AI assistants to interact with the M-Team private torrent tracker API for searching resources, retrieving torrent details, and downloading torrent files. It provides a bridge for Model Context Protocol clients to manage and access private tracker content through natural language.

Provides comprehensive access to People Data Labs' data models and search capabilities, enabling enrichment of person and company profiles, multi-criteria searches, and autocomplete functionality through a Model Context Protocol interface.