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Synapse — Research Orchestration

Research Orchestration for Human Researchers and AI Agents

中文

Synapse is a research orchestration platform that brings human researchers and AI agents together. It manages the full research lifecycle — from literature review and question formulation through experiment execution and report generation — with built-in agent management, compute orchestration, and real-time observability.

Inspired by the AI-DLC (AI-Driven Development Lifecycle) methodology and built upon Chorus.


Table of Contents

Research Workflow

Research Project ──> Research Questions ──> Experiments ──> Reports
       ^                   ^                    ^              ^
    Human              Human or            AI Agent         AI Agent
    creates            AI Agent            executes &       writes
    project            proposes            reports          analysis
                                           progress

Four agent permission roles (composable):

Permission Responsibility
Pre-research Literature search, related works discovery via Semantic Scholar
Research Propose research questions, hypothesis formulation
Experiment Execute experiments, allocate compute, report progress
Report Generate experiment reports, literature reviews, synthesis documents

The Autonomous Loop enables a self-sustaining research cycle: when all experiment queues are empty, the assigned agent analyzes the full project context and proposes new experiments for human review.


Features

Agent Management

Dedicated /agents page with 4 composable permissions. Each agent gets an API key for MCP tool access. Agents are owned per-user with full isolation.

Related Works & Literature Search

Project-level literature management:

  • Manual addition — paste an arXiv URL, metadata auto-fetched via Semantic Scholar
  • Auto-search — assign a pre_research agent to discover papers automatically
  • Deep Research — generate a comprehensive literature review document

Experiments Board

Five-column Kanban board (Draft → Pending Review → Pending Start → In Progress → Completed) with:

  • Live status badges — sent / ack / checking resources / queuing / running
  • Progress timeline — agents report step-by-step via synapse_report_experiment_progress
  • Autonomous Loop toggle — agent proposes new experiments when queues are empty

Agent-Generated Reports

On experiment completion, the assigned agent writes its own report — analyzing results in the context of the project's goals, in the project's language. Replaces template-based document generation.

Compute Orchestration

  • GPU pool management with node/GPU inventory
  • Per-project compute pool binding (strong constraint on GPU reservations)
  • Managed SSH key bundles for secure agent access to compute nodes
  • Dynamic agent timeout based on experiment compute budget

Research Questions Canvas

Hierarchical question board with parent-child relationships, status progression (open → elaborating → experiment created → completed), and linked experiment tracking.

Notification System

Real-time SSE delivery with Redis Pub/Sub for cross-instance propagation. Preferences grouped by agent permission categories. Agents receive notifications for assignments, mentions, and autonomous loop triggers.

MCP Tools

30+ MCP tools covering the full research workflow:

Category Tools
Read synapse_get_research_project, synapse_get_experiment, synapse_get_assigned_experiments, synapse_get_project_full_context
Literature synapse_search_papers, synapse_add_related_work, synapse_get_related_works
Experiment synapse_start_experiment, synapse_submit_experiment_results, synapse_report_experiment_progress
Compute synapse_list_compute_nodes, synapse_get_node_access_bundle, synapse_sync_node_inventory
Autonomous synapse_propose_experiment
Collaboration synapse_add_comment, synapse_get_comments

Getting Started

Quick Start with Docker

git clone https://github.com/Vincentwei1021/Synapse.git
cd Synapse

export DEFAULT_USER=admin@example.com
export DEFAULT_PASSWORD=changeme
docker compose up -d

Open http://localhost:3000 and log in.

Local Development

Prerequisites: Node.js 22+, pnpm 9+, PostgreSQL

cp .env.example .env
# Edit .env to configure DATABASE_URL

pnpm install
pnpm db:push
pnpm dev

open http://localhost:3000

Connect AI Agents

Option 1: OpenClaw Plugin (Recommended)

Set environment variables:

export SYNAPSE_URL="http://localhost:3000"
export SYNAPSE_API_KEY="syn_your_api_key"

Install from Plugin Marketplace:

claude
/plugin marketplace add Synapse-AIDLC/synapse
/plugin install synapse@synapse-plugins

Option 2: Manual MCP Configuration

Create .mcp.json in your project root:

{
  "mcpServers": {
    "synapse": {
      "type": "http",
      "url": "http://localhost:3000/api/mcp",
      "headers": {
        "Authorization": "Bearer syn_your_api_key"
      }
    }
  }
}

Deploy to AWS

./install.sh

The interactive installer provisions: VPC, Aurora Serverless v2 (PostgreSQL), ElastiCache Serverless (Redis), ECS Fargate, and ALB with HTTPS.


Documentation

Document Description
CLAUDE.md Development guide and coding conventions
Architecture Technical architecture
MCP Tools MCP tools reference
OpenClaw Plugin Plugin design and hooks
Docker Docker deployment guide

License

AGPL-3.0 — see LICENSE.txt

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AI Research orchestration platform where human researchers and AI agents collaborate on experiments, literature review, and report generation.

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