Councly MCP Server
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., "@Councly MCP Servercreate a council hearing to review this code for security vulnerabilities"
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.
@councly/mcp
MCP (Model Context Protocol) server for Councly - Multi-LLM Council Hearings.
Enable Claude Code, Codex, and other MCP-compatible AI assistants to invoke council hearings where multiple LLMs (Claude, GPT, Gemini, Grok) debate topics and synthesize verdicts.
Installation
npm install -g @councly/mcpOr use directly with npx:
npx @councly/mcpSetup
1. Get an API Key
Sign in to Councly
Go to Settings > MCP Integration
Create a new API key
Copy the key (shown only once)
2. Configure Claude Code
Add to your Claude Code settings (~/.claude/settings.json):
{
"mcpServers": {
"councly": {
"command": "npx",
"args": ["@councly/mcp"],
"env": {
"COUNCLY_API_KEY": "cnc_your_key_here"
}
}
}
}3. Configure Codex CLI
export COUNCLY_API_KEY=cnc_your_key_hereOr add to your shell profile.
Tools
councly_hearing
Create a council hearing where multiple LLMs debate a topic.
Parameters:
Parameter | Type | Required | Default | Description |
subject | string | Yes | - | The topic to discuss (10-10000 chars) |
preset | string | No | balanced | Model preset: |
workflow | string | No | auto | Workflow: |
wait | boolean | No | true | Wait for completion |
timeout_seconds | number | No | 300 | Max wait time (30-600) |
Presets:
Preset | Credits | Counsels | Best For |
balanced | 9 | 3 | General purpose discussions |
fast | 6 | 3 | Quick responses, simple topics |
coding | 14 | 3 | Code review, technical decisions |
coding_plus | 17 | 4 | Complex code problems |
Example:
Use councly_hearing with subject="Review this Python function for security issues:
def authenticate(username, password):
query = f'SELECT * FROM users WHERE username='{username}' AND password='{password}''
return db.execute(query)
" and preset="coding"councly_status
Check the status of a hearing.
Parameters:
Parameter | Type | Required | Description |
hearing_id | string (uuid) | Yes | The hearing ID |
Example:
Use councly_status with hearing_id="550e8400-e29b-41d4-a716-446655440000"Response Format
Completed hearings return:
Status: completed, failed, or early_stopped
Verdict: Synthesized conclusion from the moderator
Trust Score: 0-100 confidence rating
Counsel Perspectives: Summary from each counsel
Cost: Credits used
Error Handling
Common errors:
Code | Description |
INSUFFICIENT_BALANCE | Not enough credits |
ACTIVE_HEARING_EXISTS | One hearing already in progress |
RATE_LIMIT_EXCEEDED | Too many requests |
CONTENT_BLOCKED | Subject contains prohibited content |
Environment Variables
Variable | Required | Description |
COUNCLY_API_KEY | Yes | Your MCP API key |
COUNCLY_BASE_URL | No | API base URL (default: https://councly.ai) |
Pricing
Councly uses a credit-based pricing model:
1 credit = $0.01 USD
Credits are deducted at hearing creation
Failed hearings are refunded
Purchase credits at councly.ai/billing.
Links
License
Apache 2.0 - See LICENSE
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/slmnsrf/councly-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server