# Multi-Agent Quorum Configuration Example
#
# This demonstrates configuring a multi-agent system with a planner
# coordinating specialist agents.

[quorum]
cwd = "."
delegation = true
verification = true

# Global MCP servers (available to all agents)
[[mcp]]
name = "github"
transport = "stdio"
command = "npx"
args = ["-y", "@anthropic/mcp-server-github"]
env = { GITHUB_TOKEN = "${GITHUB_TOKEN}" }

# Planner agent configuration
[planner]
provider = "openai"
model = "${PLANNER_MODEL:-gpt-4}"
# api_key = "${OPENAI_API_KEY}"

tools = [
    "delegate",
    "create_task", "read_task", "update_task", "complete_task",
    "read_tool",
    "index",
    "search_text",
    "github.*"  # All tools from github MCP
]

system = [{ file = "prompts/planner.md" }]

# Delegate agents
[[delegates]]
id = "coder"
provider = "ollama"
model = "devstral:latest"
description = "Expert coder for implementation tasks"
capabilities = ["rust", "python", "typescript"]

tools = [
    "edit",
    "shell",
    "read_tool",
    "index",
    "write_file",
    "glob",
    "search_text"
]

system = [{ file = "prompts/coder.md" }]

# Inline MCP for this delegate only
# [[delegates.mcp]]
# name = "local_fs"
# transport = "stdio"
# command = "./my-fs-server"

[[delegates]]
id = "researcher"
provider = "anthropic"
model = "claude-3-sonnet"
description = "Research specialist for information gathering"
capabilities = ["research", "browse"]

tools = [
    "browse",
    "read_tool",
    "github.search_repos",  # Specific tool from github MCP
    "github.list_issues"
]

system = "You are a research specialist. Find accurate, up-to-date information from reliable sources."