AI Agents, MCP, and Skills

gflow can run as a local stdio MCP server, allowing agent CLIs such as Claude Code, Codex, and OpenCode to treat scheduler operations as tool calls instead of rewriting shell commands every time.

Use this as the MCP server command in your agent configuration:

gflow mcp serve

gflow mcp serve is a local stdio server command. MCP clients typically launch stdio servers as local child processes using the configured command and arguments.

Before connecting any agent CLI, first make sure the local scheduler is healthy:

gflowd up
gflowd status
ginfo

• gflowd must be started first.
• If gflow is not on PATH, use an absolute path instead.
• To confirm the MCP subcommand is available, run gflow mcp serve --help.

Claude Code

User-scope configuration is recommended:

claude mcp add --scope user gflow -- gflow mcp serve

Common check commands:

claude mcp list
claude mcp get gflow

Notes:

• If you want the configuration to apply only to the current project, change --scope user to --scope project.
• If gflow is not on PATH, switch to an absolute path, for example -- /home/you/.local/bin/gflow mcp serve.

Example CLAUDE.md:

# gflow workflow

- Use the `gflow` MCP server for queue, job, and log operations.
- Prefer read operations before mutating scheduler state.
- Ask before submit, cancel, hold, release, or update unless the user already asked for it.
- When a job fails, summarize the key log lines before proposing a retry.

Codex

Minimal configuration:

codex mcp add gflow -- gflow mcp serve

View the current configuration:

codex mcp list
codex mcp get gflow

You can also write it directly to ~/.codex/config.toml:

[mcp_servers.gflow]
command = "gflow"
args = ["mcp", "serve"]

Notes:

• If gflow is not on PATH, change command to an absolute path.

Example AGENTS.md:

## gflow

- Use the `gflow` MCP server for scheduler actions when available.
- Prefer read tools before writes.
- Confirm destructive job actions unless the user explicitly asked for them.
- Include job id, requested GPUs, and recent log evidence when reporting failures.

OpenCode

OpenCode usually declares MCP directly in its config file. The global config is typically at ~/.config/opencode/opencode.json, and a project-level config can be placed at opencode.json in the repository root. Both also support JSONC.

Minimal example:

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "gflow": {
      "type": "local",
      "command": ["gflow", "mcp", "serve"],
      "enabled": true
    }
  }
}

Check connection status:

opencode mcp list

Notes:

• OpenCode local MCP uses type: "local" and a command array.
• If gflow is not on PATH, change command to an absolute-path array.

FAQ

MCP is already added, but the agent cannot see the gflow tools

Check these first:

gflowd status
ginfo
gflow mcp serve --help

Common causes:

• gflowd is not running.
• gflow is not on the PATH seen by the agent process.
• The local config points to the wrong daemon address or port.
• If you start gflow mcp serve directly in a shell, it will wait for stdio traffic from an MCP client.

See Also

• Configuration
• Job Submission
• Tips
• gflowd Reference