Bohan Jiang d39da9f7f0 MUL-2764: feat(agents): add MCP config tab to agent detail page (#3419)
* MUL-2764: feat(agents): add MCP config tab to agent detail page

Backend already stores `mcp_config` and the daemon forwards it to the
runtime CLI via `--mcp-config`; this only adds the UI entry point.

The new tab presents a JSON editor that pretty-prints the existing
config, validates the buffer on every keystroke, and saves through the
existing `PUT /api/agents/{id}` path. Clearing the editor sends
`mcp_config: null`, which the handler reads as "wipe the column" and
the daemon falls back to the CLI's own default.

When the caller can't see secrets (agent actor, or a non-owner
non-admin member), the server already returns `mcp_config: null` with
`mcp_config_redacted: true`; the tab renders a read-only "configured
but hidden" state in that case so a non-privileged member cannot
silently overwrite an admin-owned config by saving an empty editor.

Co-authored-by: multica-agent <github@multica.ai>

* fix(agents): MCP tab — preserve in-flight edits + warn non-Claude runtimes

- Fix stale-editor sync: compare the local draft against the *previous*
  original via a ref, so a background agent refetch updates an untouched
  editor instead of being silently ignored. Without this, a draft equal to
  the OLD original was treated as user-edited after the prop changed, and
  the next Save would write the old config back over a concurrent admin
  edit.
- Surface a notice inside the tab when the agent's runtime provider is not
  Claude — today's daemon only forwards mcp_config via Claude's
  --mcp-config, so saving on e.g. a Codex agent was silent but ineffective.
- Tests for both: rerender resyncs an untouched editor, rerender preserves
  an in-flight edit, warning renders on non-Claude / hides on Claude.

MUL-2764

Co-authored-by: multica-agent <github@multica.ai>

* MUL-2764: feat(agents): codex MCP support + hide MCP tab on unsupported runtimes

- Backend: codex.go now translates agent.mcp_config (Claude-style
  `{"mcpServers": {...}}`) into `-c mcp_servers.<name>=<inline-toml>`
  flags for `codex app-server`, so MCP servers configured in the UI
  reach Codex's per-task config layer. Bad mcp_config JSON downgrades
  to a warn-and-skip so it can't break the agent launch.
- Frontend: AgentOverviewPane hides the MCP tab when the agent's
  runtime provider doesn't read mcp_config — only `claude` and `codex`
  are supported today, every other provider sees no MCP tab. The
  previous in-tab warning is removed (no longer reachable).
- New shared helper `providerSupportsMcpConfig` lives in
  `@multica/core/agents` so views and any future caller share one list
  of MCP-aware providers.
- Tests: new go-side coverage for stdio + url + multi-server inputs,
  TOML string escaping, malformed-input fallback, and arg ordering vs
  custom_args; new views-side coverage for which providers surface the
  MCP tab. En + zh-Hans copy and parity test refreshed.

Co-authored-by: multica-agent <github@multica.ai>

* MUL-2764: fix(agents): keep codex mcp_config secrets out of argv/logs

Move the agent's mcp_config from a `-c mcp_servers.<id>=<inline-toml>`
argv flag into a daemon-managed `[mcp_servers.*]` block inside the
per-task `$CODEX_HOME/config.toml`. mcp_servers.<id>.env is a documented
Codex config field and the UI already treats mcp_config as redacted for
non-admins; argv would have leaked those values into `ps aux` and the
`agent command` log line. The file is forced to 0600 to keep secrets in
the daemon owner's lane regardless of the seed file's mode.

Also drop user-supplied `-c/--config mcp_servers.*` entries from
custom_args. Codex `-c` is last-wins (verified against codex-cli 0.132.0),
so without filtering, a custom_args entry could silently shadow whatever
the MCP Tab saved.

Strip inherited `[mcp_servers.*]` tables from the per-task config.toml
when the agent has its own mcp_config, mirroring Claude's
`--strict-mcp-config`: avoids TOML "table already exists" errors on
name collisions and matches admin expectations that the MCP Tab is the
authoritative source for that task.

Co-authored-by: multica-agent <github@multica.ai>

* MUL-2764: fix(agents): codex mcp_config three-state semantics + custom_args compat

Address the third review pass:

1. Distinguish nil vs present-but-empty mcp_config. `{}` and
   `{"mcpServers":{}}` now count as "admin saved an explicit (empty)
   managed set" — strip inherited user `[mcp_servers.*]` and pin an
   empty managed marker block. Only SQL NULL / JSON `null` map to
   "absent" and fall back to the user's global `~/.codex/config.toml`.
   This aligns Codex with the API's three-state contract (omit / null
   / object) and with Claude's `--strict-mcp-config` semantics.

2. Fail closed on `ensureCodexMcpConfig` errors and on managed
   mcp_config without CODEX_HOME. Previous warn-and-launch would
   silently inherit the user's global MCP servers and look identical
   to a successful apply — exactly the surprise the MCP Tab is meant
   to remove.

3. Only filter `-c mcp_servers.*` from `custom_args`/`extra_args`
   when the agent has a managed mcp_config. Pre-MUL-2764 agents that
   configured MCP via custom_args keep working; once an admin opts
   in via the MCP Tab the daemon owns the `mcp_servers` namespace
   and overrides are dropped (last-wins safety).

4. Update mcp_config locale intro to mention $CODEX_HOME/config.toml
   instead of the now-removed `-c mcp_servers.*` argv path.

Tests:
- Split `TestEnsureCodexMcpConfigEmptyInputsAreNoop` into
  `TestEnsureCodexMcpConfigAbsentLeavesUserTablesAlone` (nil/null)
  and `TestEnsureCodexMcpConfigEmptyManagedSetStripsUserMcp` (`{}`,
  `{"mcpServers":{}}`).
- Add `TestEnsureCodexMcpConfigEmptyManagedSetIdempotent` to pin
  byte-identical reruns on the empty managed marker block.
- Add `TestHasManagedCodexMcpConfig` covering the eight relevant
  inputs.
- Add `TestBuildCodexArgsPreservesCustomMcpOverridesWhenUnmanaged`
  and `TestBuildCodexArgsDropsCustomMcpOverridesWhenManaged` to
  pin the new gating.
- Add `TestCodexExecuteFailsClosedWhenMcpConfigInvalid` and
  `TestCodexExecuteFailsClosedWhenManagedMcpButNoCodexHome` for the
  Execute paths.

Co-authored-by: multica-agent <github@multica.ai>

---------

Co-authored-by: J <j@multica.ai>
Co-authored-by: multica-agent <github@multica.ai>
2026-05-28 15:11:28 +08:00

Multica — humans and agents, side by side

Multica

Multica

Your next 10 hires won't be human.

The open-source managed agents platform.
Turn coding agents into real teammates — assign tasks, track progress, compound skills.

CI GitHub stars

Website · Cloud · X · Self-Hosting · Contributing

English | 简体中文

What is Multica?

Multica turns coding agents into real teammates. Assign issues to an agent like you'd assign to a colleague — they'll pick up the work, write code, report blockers, and update statuses autonomously.

No more copy-pasting prompts. No more babysitting runs. Your agents show up on the board, participate in conversations, and compound reusable skills over time. Think of it as open-source infrastructure for managed agents — vendor-neutral, self-hosted, and designed for human + AI teams. Works with Claude Code, Codex, GitHub Copilot CLI, OpenClaw, OpenCode, Hermes, Gemini, Pi, Cursor Agent, Kimi, and Kiro CLI.

For larger teams, Squads add a stable routing layer: assign work to a group led by an agent, and the leader delegates to the right member.

Multica board view

Why "Multica"?

Multica — Multiplexed Information and Computing Agent.

The name is a nod to Multics, the pioneering operating system of the 1960s that introduced time-sharing — letting multiple users share a single machine as if each had it to themselves. Unix was born as a deliberate simplification of Multics: one user, one task, one elegant philosophy.

We think the same inflection is happening again. For decades, software teams have been single-threaded — one engineer, one task, one context switch at a time. AI agents change that equation. Multica brings time-sharing back, but for an era where the "users" multiplexing the system are both humans and autonomous agents.

In Multica, agents are first-class teammates. They get assigned issues, report progress, raise blockers, and ship code — just like their human colleagues. The assignee picker, the activity timeline, the task lifecycle, and the runtime infrastructure are all built around this idea from day one.

Like Multics before it, the bet is on multiplexing: a small team shouldn't feel small. With the right system, two engineers and a fleet of agents can move like twenty.

Features

Multica manages the full agent lifecycle: from task assignment to execution monitoring to skill reuse.

  • Agents as Teammates — assign to an agent like you'd assign to a colleague. They have profiles, show up on the board, post comments, create issues, and report blockers proactively.
  • Squads — group agents (and humans) under a leader agent and assign work to the squad. The leader decides who should pick it up, so routing stays stable as the team grows. @FrontendTeam instead of @alice-or-bob-or-carol.
  • Autonomous Execution — set it and forget it. Full task lifecycle management (enqueue, claim, start, complete/fail) with real-time progress streaming via WebSocket.
  • Autopilots — schedule recurring work for agents. Cron triggers, webhooks, or manual runs — each autopilot creates the issue and routes it to an agent automatically, so daily standups, weekly reports, and periodic audits run themselves.
  • Reusable Skills — every solution becomes a reusable skill for the whole team. Deployments, migrations, code reviews — skills compound your team's capabilities over time.
  • Unified Runtimes — one dashboard for all your compute. Local daemons and cloud runtimes, auto-detection of available CLIs, real-time monitoring.
  • Multi-Workspace — organize work across teams with workspace-level isolation. Each workspace has its own agents, issues, and settings.

Quick Install

brew install multica-ai/tap/multica

Use brew upgrade multica-ai/tap/multica to keep the CLI current.

macOS / Linux (install script)

curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash

Use this if Homebrew is not available. The script installs the Multica CLI on macOS and Linux by using Homebrew when it is on PATH, otherwise it downloads the binary directly.

Windows (PowerShell)

irm https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.ps1 | iex

Then configure, authenticate, and start the daemon in one command:

multica setup          # Connect to Multica Cloud, log in, start daemon

Self-hosting? Add --with-server to deploy a full Multica server on your machine:

curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash -s -- --with-server
multica setup self-host

This pulls the official Multica images from GHCR (latest stable by default). Requires Docker. See the Self-Hosting Guide for details. If the selected GHCR tag has not been published yet, fall back to make selfhost-build from a checkout.


Getting Started

1. Set up and start the daemon

multica setup           # Configure, authenticate, and start the daemon

The daemon runs in the background and auto-detects agent CLIs (claude, codex, copilot, openclaw, opencode, hermes, gemini, pi, cursor-agent, kimi, kiro-cli) on your PATH.

2. Verify your runtime

Open your workspace in the Multica web app. Navigate to Settings → Runtimes — you should see your machine listed as an active Runtime.

What is a Runtime? A Runtime is a compute environment that can execute agent tasks. It can be your local machine (via the daemon) or a cloud instance. Each runtime reports which agent CLIs are available, so Multica knows where to route work.

3. Create an agent

Go to Settings → Agents and click New Agent. Pick the runtime you just connected and choose a provider (Claude Code, Codex, GitHub Copilot CLI, OpenClaw, OpenCode, Hermes, Gemini, Pi, Cursor Agent, Kimi, or Kiro CLI). Give your agent a name — this is how it will appear on the board, in comments, and in assignments.

4. Assign your first task

Create an issue from the board (or via multica issue create), then assign it to your new agent. The agent will automatically pick up the task, execute it on your runtime, and report progress — just like a human teammate.


CLI

The multica CLI connects your local machine to Multica — authenticate, manage workspaces, and run the agent daemon.

Command Description
multica login Authenticate (opens browser)
multica daemon start Start the local agent runtime
multica daemon status Check daemon status
multica setup One-command setup for Multica Cloud (configure + login + start daemon)
multica setup self-host Same, but for self-hosted deployments
multica workspace list List your workspaces (current is marked with *)
multica workspace switch <id|slug> Switch the default workspace for this profile
multica issue list List issues in your workspace
multica issue create Create a new issue
multica update Update to the latest version

See the CLI and Daemon Guide for the full command reference.


Architecture

┌──────────────┐     ┌──────────────┐     ┌──────────────────┐
│   Next.js    │────>│  Go Backend  │────>│   PostgreSQL     │
│   Frontend   │<────│  (Chi + WS)  │<────│   (pgvector)     │
└──────────────┘     └──────┬───────┘     └──────────────────┘
                            │
                     ┌──────┴───────┐
                     │ Agent Daemon │  runs on your machine
                     └──────────────┘  (Claude Code, Codex, GitHub Copilot CLI,
                                        OpenCode, OpenClaw, Hermes, Gemini,
                                        Pi, Cursor Agent, Kimi, Kiro CLI)
Layer Stack
Frontend Next.js 16 (App Router)
Backend Go (Chi router, sqlc, gorilla/websocket)
Database PostgreSQL 17 with pgvector
Agent Runtime Local daemon executing Claude Code, Codex, GitHub Copilot CLI, OpenClaw, OpenCode, Hermes, Gemini, Pi, Cursor Agent, Kimi, or Kiro CLI

Development

For contributors working on the Multica codebase, see the Contributing Guide.

Prerequisites: Node.js v20+, pnpm v10.28+, Go v1.26+, Docker

make dev

make dev auto-detects your environment (main checkout or worktree), creates the env file, installs dependencies, sets up the database, runs migrations, and starts all services.

See CONTRIBUTING.md for the full development workflow, worktree support, testing, and troubleshooting.

An iOS mobile client lives in apps/mobile/ — see its README for how to build it onto your own iPhone.

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