Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@multi-agent-debate-mcp Start a three-round debate on the benefits of renewable energy with pro, con, and judge agents."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
An MCP server implementation that enables structured multi-agent debates between different personas. This server allows multiple AI agents to engage in formal debates with arguments, rebuttals, and judgments across multiple rounds.
Register multiple agents with different personas (e.g., "pro", "con", "judge")
Structured debate flow with organized rounds
Colorized console output with beautiful terminal display
Flexible agent IDs beyond just "pro" and "con"
Automatic verdict tracking with rationale
Round-based system with configurable progression
Related MCP server: DebateTalk MCP
Facilitates structured multi-agent debates with arguments, rebuttals, and judgments.
Inputs:
agentId (string): Unique identifier for the agent (e.g., "pro", "con", "judge")
round (integer): Current debate round number (≥1)
action (string): One of "register", "argue", "rebut", "judge"
content (string, optional): The argument text or verdict content
targetAgentId (string, optional): For rebuttals, specify which agent is being countered
needsMoreRounds (boolean): Whether additional debate rounds are needed
The Multi-Agent Debate tool is designed for:
Structured debates between multiple AI personas
Formal argumentation with rebuttals and counterpoints
Multi-round discussions with judgment phases
Complex decision-making processes requiring multiple perspectives
Educational debate simulations
Collaborative problem-solving through adversarial discussion
{
"mcpServers": {
"multi-agent-debate": {
"command": "npx",
"args": [
"-y",
"multi-agent-debate-mcp"
]
}
}
}{
"mcpServers": {
"multi-agent-debate": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"ghcr.io/albinjal/multi-agent-debate-mcp:latest"
]
}
}
}
Structured multi‑persona debate tool.
Call sequence (typical):
Each persona registers once with action:"register".
Personas alternate action:"argue" (fresh point) or "rebut" (counter a targetAgentId).
A special persona (or either side) issues action:"judge" with a verdict text (first line should be "pro", "con", or "inconclusive").
Set needsMoreRounds:false only when the debate is finished and a verdict stands.
Parameters:
agentId (string) : "pro", "con", "judge", or any custom ID
round (int ≥1) : Debate round number
action (string) : "register" | "argue" | "rebut" | "judge"
content (string, optional) : Argument text or verdict
targetAgentId (string opt.) : Agent being rebutted (only for action:"rebut")
needsMoreRounds (boolean) : True if additional debate rounds desired
| Name | Required | Description | Default |
|---|---|---|---|
| agentId | Yes | ||
| round | Yes | ||
| action | Yes | ||
| content | No | ||
| targetAgentId | No | ||
| needsMoreRounds | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explains the protocol and verdict format, but does not explicitly disclose state management, side effects, or error behavior, which are relevant for such a tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with numbered steps and a parameter list, making it easy to follow. It is appropriately detailed, though slightly lengthy; could be condensed without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity and the absence of an output schema, the description covers the essential protocol and parameter semantics. It does not detail return values or error handling, but the sequence and usage are sufficiently explained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by listing each parameter with explanations, including the enum values for action, the meaning of content and targetAgentId, and the role of needsMoreRounds.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as a 'Structured multi-persona debate tool' and explains the call sequence with specific actions, making it distinct even without siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a typical call sequence (steps 1-4) and explains when to use each action (register, argue, rebut, judge) and when to set needsMoreRounds to false. However, it lacks explicit when-not-to-use guidance or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.7multiagentdebateOnly one tool exists, so there is no risk of confusion with other tools. The tool's purpose is clearly singular.
With a single tool, naming consistency is trivially maintained. The name 'multiagentdebate' is descriptive and unambiguous.
One tool for a multi-step debate process feels thin. While the tool is comprehensive in its actions, it would benefit from splitting into separate tools for registration, arguing, and judging to improve modularity.
The tool covers the core debate actions but lacks tools for listing debates, retrieving histories, or managing multiple concurrent debates. This creates significant gaps for an agent trying to orchestrate complex workflows.
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Multi-model AI debates: GPT-4o, Claude, Gemini & 200+ models discuss, then synthesize insight.
Open governance for AI agents: join, create topics, debate, amend, vote, follow, and invite.
Build, validate, and deploy multi-agent AI solutions from any AI environment.
Durable agent-to-agent handoffs and shared scratchpad for multi-agent workflows.
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