Documentation Index
Fetch the complete documentation index at: https://docs.monolex.ai/llms.txt
Use this file to discover all available pages before exploring further.
connector.json vs MCP
Different Layers, Same Ecosystem
connector.json: AI ↔ AI (orchestration — who does what, when, where)
MCP: AI → tool (access — connect to a service, call a function)
They solve different problems and work together.
MCP (Model Context Protocol) lets AI connect to external tools and data:
{
"mcpServers": {
"github": { "command": "npx", "args": ["@anthropic/mcp-github"] },
"postgres": { "command": "npx", "args": ["@anthropic/mcp-postgres"] }
}
}
- AI calls
github.create_pr() → MCP sends request → GitHub API → response
- AI calls
postgres.query() → MCP sends request → database → results
The target is passive. Tools don’t initiate. They respond.
connector.json: AI Orchestration Spec
connector.json lets AI coordinate with other AI:
{
"models": { "primary": "claude", "review": "codex" },
"pipeline": {
"phases": [
{ "name": "implement", "model": "primary" },
{ "name": "review", "model": "review" }
]
}
}
- Claude implements → Codex reviews → results synthesized
- Both are active participants. Both reason, decide, act.
The target is active. Other AI agents that think and respond intelligently.
How They Compose
connector.json includes MCP as a tool configuration:
{
"connector": "2.0",
"models": { "primary": "claude" },
"tools": {
"mcp": ["github", "postgres", "chrome-devtools"]
},
"pipeline": {
"phases": [
{
"name": "investigate",
"model": "primary",
"prompt": "Use GitHub MCP to find recent PRs. Use Postgres MCP to check migration status."
}
]
}
}
MCP servers are available inside connector.json sessions.
The AI worker can use MCP tools while participating in the connector pipeline.
Comparison Table
| MCP | connector.json |
|---|
| What it connects | AI → tools/data | AI ↔ AI |
| Target | Passive (responds) | Active (reasons) |
| Direction | One-way request-response | Multi-directional collaboration |
| Protocol | JSON-RPC over stdio/SSE | JSON spec → PTY sessions |
| Session isolation | Not applicable | worktree, sandbox per session |
| Cost routing | Not applicable | Route by model cost/capability |
| Failover | Not applicable | Switch to different LLM |
| Multi-phase | Not applicable | Pipeline with sequential phases |
| Cross-machine | Server can be remote | Workers on different machines |
| Standard body | Anthropic-led | OpenCLIs / Monolex |
Layer Diagram
┌─────────────────────────────────────────────┐
│ connector.json (orchestration) │
│ Models, pipeline, session isolation │
│ ┌─────────────────────────────────────┐ │
│ │ MCP (tool access) │ │
│ │ github, postgres, chrome, slack │ │
│ └─────────────────────────────────────┘ │
│ ┌─────────────────────────────────────┐ │
│ │ PTY-for-AI (execution) │ │
│ │ daemon, headless, session plugins │ │
│ └─────────────────────────────────────┘ │
└─────────────────────────────────────────────┘
connector.json sits on top. MCP and PTY-for-AI are execution layers inside it.