RabbitMQ MCP server
Project description
rabbitmq-mcp
RabbitMQ MCP server for management and AMQP operations, with OpenAPI-driven call_id execution and semantic search.
Features
- MCP tools:
search_ids/get_id/call_id - OpenAPI-driven full HTTP management API calls
- Semantic search (optional embeddings, keyword fallback when dependencies are missing)
- Request/response validation (Pydantic first, jsonschema fallback)
- Destructive operation safety guard (disabled by default)
- AMQP:
publish/consume/ack/nack/reject
Requirements
- Python 3.12+
- RabbitMQ Management Plugin (Management API)
Install & Run
Using uvx
uvx rabbitmq-mcp \
--host localhost \
--port 15672 \
--user admin \
--password admin123 \
--allow-destructive false
From source
uv run --project . rabbitmq-mcp \
--host localhost \
--port 15672 \
--user admin \
--password admin123 \
--allow-destructive false
CLI Parameters
Required:
--host--port--user--password--allow-destructive(true|false)
Optional (with defaults):
--amqp-port(default5672)--vhost(default/)--scheme(defaulthttp)--verify-ssl(default inferred fromscheme)--timeout(default10.0)--max-connections(default20)--max-keepalive(default10)--retries(default1)--retry-backoff(default0.2)--vhost-cache-ttl(default60)
MCP Tools
search_ids: Search operationId by keyword/semantics (pagination supported).get_id: Return input/output schema for the given operationId.call_id: Execute the operationId (HTTP/AMQP auto routing).
MCP Config Example
Example JSON config for MCP clients that accept command/args (e.g., Claude Desktop):
{
"mcpServers": {
"rabbitmq": {
"command": "uvx",
"args": [
"rabbitmq-mcp",
"--host",
"localhost",
"--port",
"15672",
"--user",
"admin",
"--password",
"CHANGE_ME",
"--allow-destructive",
"false"
]
}
}
}
Generation & Validation Scripts
# Validate OpenAPI
uv run --project . validate-openapi
# Generate Pydantic schemas
uv run --project . generate-schemas
# Generate registry
uv run --project . python scripts/generate_registry.py
# Generate embeddings (requires vector extra)
uv run --project . --extra vector python scripts/generate_embeddings.py
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