deepmiro
Simulate hundreds of AI agents to predict how communities react to events and policies.
От сообщества: Добавлен пользователем или импортирован; проверьте владельца перед подключениемРаботаетБез входаГлобальныйБесплатноТолько чтение
Что умеет
- Create Simulation: Run a full swarm prediction. Builds a knowledge graph, generates agent personas, runs a multi-agent social media simulation, and generates a prediction report. Streams progress upda
- Simulation Status: Check the progress of a running or completed simulation. Returns phase-aware status with entity names and action content. Phases: building_graph → generating_profiles → simulating →
- Get Report: Generate and retrieve the prediction report for a completed simulation. If the report hasn't been generated yet, triggers generation (may take 1-3 minutes). Returns a detailed markdown ana
Какие данные видит
Нужен ли аккаунт
Не нужен: сервер работает без входа
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.
Список инструментов сервера (9)
Технические названия из tools/list. Нужны только разработчикам.
| create_simulation | Run a full swarm prediction. Builds a knowledge graph, generates agent personas, runs a multi-agent social media simulation, and generates a prediction report. Streams progress updates. Returns the final report when complete. |
| simulation_status | Check the progress of a running or completed simulation. Returns phase-aware status with entity names and action content. Phases: building_graph → generating_profiles → simulating → completed. |
| get_report | Generate and retrieve the prediction report for a completed simulation. If the report hasn't been generated yet, triggers generation (may take 1-3 minutes). Returns a detailed markdown analysis of the simulation results. |
| interview_agent | Chat with a specific simulated agent to understand their perspective, reasoning, and predicted behavior. The agent responds in character based on their persona and simulation experience. |
| list_simulations | List past simulation runs with their status and metadata. |
| search_simulations | Search past simulations by topic, project name, or simulation ID. |
| quick_predict | Fast, lightweight prediction without running a full simulation. Uses the LLM to simulate swarm behavior and predict outcomes. Returns in seconds. For deeper analysis, use create_simulation instead. |
| upload_document | Upload a document for use in simulations. LIMITS: Max 10MB, PDF/MD/TXT only. The server extracts text server-side (PyMuPDF for PDFs). Returns a document_id to pass to create_simulation. NOTE: Only works with local file paths (stdio transport). For remote/hosted mode, the client skill uploads via HTTP instead. |
| simulation_data | Access raw simulation data: agent profiles, configuration, action logs, social media posts, round-by-round timeline, per-agent activity stats, and interview history. Use this to inspect what happened during a simulation. |