Confer — System architecture

High-level architecture

┌────────────────────────────────────────────────────────────┐
│  Clients (Tauri 2.0)                                       │
│  iOS · Android · Windows · macOS · Linux                   │
└──────────────────────────┬─────────────────────────────────┘
                           │ WSS / HTTPS / SSE
                           ▼
┌────────────────────────────────────────────────────────────┐
│  Edge API Gateway  (Bun + Hono)                            │
│  Auth · Rate limit · Routing · WS fan-out                  │
└─────┬─────────────┬─────────────────┬────────────────┬─────┘
      │             │                 │                │
      ▼             ▼                 ▼                ▼
 ┌────────┐  ┌─────────────┐  ┌────────────┐  ┌──────────────┐
 │ Agent  │  │Conversation │  │ Identity & │  │ MCP / Tools  │
 │Runtime │  │     Hub     │  │A2A Gateway │  │  Connector   │
 └───┬────┘  └──────┬──────┘  └─────┬──────┘  └──────┬───────┘
     │              │               │                │
     ▼              ▼               ▼                ▼
┌──────────────────────────────────────────────────────────────┐
│  Data layer: PostgreSQL · Redis · NATS · Vector (Qdrant)·S3 │
└──────────────────────────────────────────────────────────────┘
       │                              │
       ▼                              ▼
 LLM providers              Other instances' Agents
 (Claude / GPT /            (federation via A2A
  DeepSeek / Qwen)           over HTTPS)

Design principles

• Stateless edge, stateful core: the gateway is stateless and horizontally scalable; the Agent runtime is sharded by user, with state held in PG/Redis
• Federation-ready from day 1: with DID:web identity + AgentFacts, even a single instance runs on the federation protocol, so future federation incurs zero migration cost
• BYO LLM key: the platform does not bear LLM costs; users bring their own API key
• Protocol-first: core interactions use open protocols (A2A, MCP, DID:web, NANDA AgentFacts) rather than being locked into a proprietary protocol
• Bun + TypeScript full stack: the backend is Bun + Hono and the client is Tauri + React, so types can be shared

Service boundaries

1. Edge API Gateway

See docs/05-api.md.

• Responsibilities: TLS termination, dual user/A2A authentication, four-dimensional rate limiting, HTTP/WS/SSE routing, multi-device fan-out
• Tech stack: Bun + Hono
• Key dependencies: JWKS (user token verification), DID document cache, NATS (fan-out)
• Does not do: business logic, persisting business data, calling the LLM

2. Agent Runtime

Each user maps to one resident Agent instance.

• Responsibilities:
  • Maintain the state of the user’s Agent (model selection, tools, policy, memory)
  • The LLM call loop (multi-provider abstraction)
  • MCP client, connecting to the tool servers the user has installed
  • Outbound A2A calls (going to negotiate with other people’s Agents)
  • The policy engine (deciding what may be disclosed to the other party)
• Lifecycle: woken on demand. When a message comes in or an A2A request arrives, it loads state from PG, runs one round, and writes back.
• Key dependencies: LLM providers, MCP servers, Identity service

3. Conversation Hub

• Responsibilities: message storage, subscription, push
• Supported conversation types:
  • User ↔ their own Agent
  • User ↔ the other party’s Agent (relayed through their own Agent)
  • User ↔ user (ordinary IM)
  • Group chat (a mix of users + Agents)
• Key dependencies: NATS Streams (persistence + fan-out), PG (message history), Redis (presence, unread counts)

4. Identity & A2A Gateway

• Responsibilities:
  • Manage the user’s DID:web document
  • Expose and cache AgentFacts
  • Handle inbound A2A requests (verifying the HTTP signature, capability token)
  • Forward outbound A2A requests
  • Rate limiting and anti-spam for federation peers
• Key dependencies: PG (DID/peer cache), Redis (counter-based rate limiting)

For the detailed protocol design, see docs/03-protocol.md.

5. MCP / Tools Connector

• Responsibilities:
  • Connection management for the MCP tool servers the user has installed
  • The Agent runtime calls tools through here
  • Standardized wrapping of tool-call results
• Key dependencies: @modelcontextprotocol/sdk

Data layer

Client architecture

• Foundation: Tauri 2.0 (Rust core + WebView rendering)
• Frontend: React 18 + TypeScript + Tailwind CSS
• State management: Zustand or Jotai (lightweight)
• Routing: TanStack Router
• Networking: native fetch + native WebSocket + EventSource (SSE)
• Local storage: SQLite + key-value store provided by Tauri (caching conversations, offline message drafts)

Cross-platform coverage

A single codebase, with no native fallback.

Claude Code plugin

See docs/06-claude-code-plugin.md.

• A standalone MCP server process, implemented with Node.js / Bun
• Users install it via claude mcp add confer <command>
• Bound to the user’s Confer account via OAuth / token

Deployment architecture

Single instance (individuals / small teams)

docker-compose.yml:
  - gateway       (Bun 服务)
  - agent-runtime (Bun 服务)
  - conversation  (Bun 服务)
  - identity      (Bun 服务)
  - postgres
  - redis
  - nats
  - qdrant
  - minio
  - caddy / traefik  (反向代理 + TLS)

Deployment: just run docker compose up -d and it works.

Enterprise instance

• A standalone deployment brought up with the same Docker Compose as above
• Uses its own domain (acme.com)
• Exposes https://acme.com/.well-known/did.json and https://acme.com/.well-known/agent.json
• Internal users log in via SSO

Cloud (Confer’s own cloud)

• Multi-tenant Kubernetes
• Each user/enterprise has its own namespace or schema
• A shared LLM provider abstraction layer (but still using the user’s own key)
• Global multi-region deployment, connecting through the nearest region

Federation (cross-instance)

Any Confer instance (self-hosted or cloud) can interoperate with other instances via the A2A protocol.

[acme.com]              [vendor-x.com]            [confer.cloud]
 Agent A    <─── A2A ───> Agent B    <─── A2A ───> Agent C

Identity and discovery:

• Each instance exposes its DID document at /.well-known/did.json
• Each Agent exposes its AgentFacts at /.well-known/agent.json
• Cross-instance search: fan-out to known instances + public registries

Observability

• Tracing: OpenTelemetry, with trace_id injected at the gateway and propagated across all services
• Logging: JSON-structured, collected by Vector / Loki
• Metrics: Prometheus, key metrics:
  • gateway_active_ws_connections{user_id}
  • agent_runtime_llm_tokens_total{provider,role}
  • a2a_inbound_requests_total{peer_domain,status}
  • mcp_tool_calls_total{tool,result}

Security boundaries

• User ↔ gateway: JWT + JWKS verification
• A2A peer ↔ gateway: HTTP Message Signatures (RFC 9421) + DID:web public key
• Internal RPC between services: mTLS or shared secret (within the Docker network)
• LLM provider calls: API keys stored encrypted (AES-256, key held in Vault / KMS)
• User file storage: S3 server-side encryption

Key technical decisions