Files
llmx/llmx-rs/docs/codex_mcp_interface.md
Sebastian Krüger c493ea1347 Phase 5: Configuration & Documentation
Updated all documentation and configuration files:

Documentation changes:
- Updated README.md to describe LLMX as LiteLLM-powered fork
- Updated CLAUDE.md with LiteLLM integration details
- Updated 50+ markdown files across docs/, llmx-rs/, llmx-cli/, sdk/
- Changed all references: codex → llmx, Codex → LLMX
- Updated package references: @openai/codex → @llmx/llmx
- Updated repository URLs: github.com/openai/codex → github.com/valknar/llmx

Configuration changes:
- Updated .github/dependabot.yaml
- Updated .github workflow files
- Updated cliff.toml (changelog configuration)
- Updated Cargo.toml comments

Key branding updates:
- Project description: "coding agent from OpenAI" → "coding agent powered by LiteLLM"
- Added attribution to original OpenAI Codex project
- Documented LiteLLM integration benefits

Files changed: 51 files (559 insertions, 559 deletions)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-11 14:45:40 +01:00

5.7 KiB
Raw Blame History

LLMX MCP Server Interface [experimental]

This document describes LLMXs experimental MCP server interface: a JSONRPC API that runs over the Model Context Protocol (MCP) transport to control a local LLMX engine.

  • Status: experimental and subject to change without notice
  • Server binary: llmx mcp-server (or llmx-mcp-server)
  • Transport: standard MCP over stdio (JSONRPC 2.0, linedelimited)

Overview

LLMX exposes a small set of MCPcompatible methods to create and manage conversations, send user input, receive live events, and handle approval prompts. The types are defined in protocol/src/mcp_protocol.rs and reused by the MCP server implementation in mcp-server/.

At a glance:

  • Conversations
    • newConversation → start a LLMX session
    • sendUserMessage / sendUserTurn → send user input into a conversation
    • interruptConversation → stop the current turn
    • listConversations, resumeConversation, archiveConversation
  • Configuration and info
    • getUserSavedConfig, setDefaultModel, getUserAgent, userInfo
    • model/list → enumerate available models and reasoning options
  • Auth
    • account/read, account/login/start, account/login/cancel, account/logout, account/rateLimits/read
    • notifications: account/login/completed, account/updated, account/rateLimits/updated
  • Utilities
    • gitDiffToRemote, execOneOffCommand
  • Approvals (server → client requests)
    • applyPatchApproval, execCommandApproval
  • Notifications (server → client)
    • loginChatGptComplete, authStatusChange
    • llmx/event stream with agent events

See code for full type definitions and exact shapes: protocol/src/mcp_protocol.rs.

Starting the server

Run LLMX as an MCP server and connect an MCP client:

llmx mcp-server | your_mcp_client

For a simple inspection UI, you can also try:

npx @modelcontextprotocol/inspector llmx mcp-server

Use the separate llmx mcp subcommand to manage configured MCP server launchers in config.toml.

Conversations

Start a new session with optional overrides:

Request newConversation params (subset):

  • model: string model id (e.g. "o3", "gpt-5", "gpt-5-llmx")
  • profile: optional named profile
  • cwd: optional working directory
  • approvalPolicy: untrusted | on-request | on-failure | never
  • sandbox: read-only | workspace-write | danger-full-access
  • config: map of additional config overrides
  • baseInstructions: optional instruction override
  • compactPrompt: optional replacement for the default compaction prompt
  • includePlanTool / includeApplyPatchTool: booleans

Response: { conversationId, model, reasoningEffort?, rolloutPath }

Send input to the active turn:

  • sendUserMessage → enqueue items to the conversation
  • sendUserTurn → structured turn with explicit cwd, approvalPolicy, sandboxPolicy, model, optional effort, and summary

Interrupt a running turn: interruptConversation.

List/resume/archive: listConversations, resumeConversation, archiveConversation.

Models

Fetch the catalog of models available in the current LLMX build with model/list. The request accepts optional pagination inputs:

  • pageSize number of models to return (defaults to a server-selected value)
  • cursor opaque string from the previous responses nextCursor

Each response yields:

  • items ordered list of models. A model includes:
    • id, model, displayName, description
    • supportedReasoningEfforts array of objects with:
      • reasoningEffort one of minimal|low|medium|high
      • description human-friendly label for the effort
    • defaultReasoningEffort suggested effort for the UI
    • isDefault whether the model is recommended for most users
  • nextCursor pass into the next request to continue paging (optional)

Event stream

While a conversation runs, the server sends notifications:

  • llmx/event with the serialized LLMX event payload. The shape matches core/src/protocol.rss Event and EventMsg types. Some notifications include a _meta.requestId to correlate with the originating request.
  • Auth notifications via method names loginChatGptComplete and authStatusChange.

Clients should render events and, when present, surface approval requests (see next section).

Approvals (server → client)

When LLMX needs approval to apply changes or run commands, the server issues JSONRPC requests to the client:

  • applyPatchApproval { conversationId, callId, fileChanges, reason?, grantRoot? }
  • execCommandApproval { conversationId, callId, command, cwd, reason? }

The client must reply with { decision: "allow" | "deny" } for each request.

Auth helpers

For the complete request/response shapes and flow examples, see the “Auth endpoints (v2)” section in the appserver README.

Example: start and send a message

{ "jsonrpc": "2.0", "id": 1, "method": "newConversation", "params": { "model": "gpt-5", "approvalPolicy": "on-request" } }

Server responds:

{ "jsonrpc": "2.0", "id": 1, "result": { "conversationId": "c7b0…", "model": "gpt-5", "rolloutPath": "/path/to/rollout.jsonl" } }

Then send input:

{ "jsonrpc": "2.0", "id": 2, "method": "sendUserMessage", "params": { "conversationId": "c7b0…", "items": [{ "type": "text", "text": "Hello LLMX" }] } }

While processing, the server emits llmx/event notifications containing agent output, approvals, and status updates.

Compatibility and stability

This interface is experimental. Method names, fields, and event shapes may evolve. For the authoritative schema, consult protocol/src/mcp_protocol.rs and the corresponding server wiring in mcp-server/.