rossum-agent 2.1.0

AI agent toolkit for Rossum: document workflows conversationally, debug pipelines automatically, and enable agentic configuration of intelligent document processing.

Rossum Agent

AI agent for Rossum document processing. Debug hooks, deploy configs, and automate workflows conversationally — powered by Claude on AWS Bedrock.

[!NOTE] This is not an official Rossum project. It is a community-developed integration built on top of the Rossum API, not a product (yet).

The agent wraps rossum-mcp with internal tools, a skills system, prompt caching, and change tracking. Interfaces: REST API, Python SDK.

Architecture

rossum-agent-api / Python SDK
  → create_agent(mcp_connection)
       → System Prompt + Skills System
       → Internal Tools
            write_file, search_knowledge_base, search_elis_docs,
            run_jq, run_grep, execute_python,
            patch_schema_with_subagent, generate_mock_pdf,
            load_skill, create_task, update_task, list_tasks,
            ask_user_question
       → Rossum MCP Server (30 tools)
            → Rossum API

The agent is a Claude Opus 4.6 loop on AWS Bedrock. Each turn loads the system prompt, auto-selects relevant MCP tool categories based on message keywords, and streams back reasoning + content + tool calls via the AI SDK UI Message Stream v1 wire protocol.

Quick Start

# Set environment variables
export ROSSUM_API_TOKEN="your-api-token"
export ROSSUM_API_BASE_URL="https://api.elis.rossum.ai/v1"
export AWS_PROFILE="default"  # For Bedrock

# Install and run
uv pip install rossum-agent[api]
rossum-agent-api

Or run from source:

git clone https://github.com/stancld/rossum-agents.git
cd rossum-agents/rossum-agent

uv sync --extra all        # All extras (api, docs, tests)
rossum-agent-api --reload

Environment Variables

Variable	Required	Description
ROSSUM_API_TOKEN	Yes	Rossum API authentication token
ROSSUM_API_BASE_URL	Yes	Base URL (e.g., https://api.elis.rossum.ai/v1)
AWS_PROFILE	Yes	AWS profile for Bedrock access
AWS_REGION	No	AWS region for Bedrock (default: us-east-1)
AWS_BEDROCK_MODEL_ARN	No	Custom ARN for the Opus model
AWS_BEDROCK_MODEL_ARN_SMALL	No	Custom ARN for the Haiku model
ROSSUM_MCP_MODE	No	MCP mode: read-write (default) or read-only
ROSSUM_AGENT_PERSONA	No	Agent persona: default or cautious
ADDITIONAL_ALLOWED_ROSSUM_HOSTS	No	Comma-separated regex patterns for additional allowed API hosts

Optional infrastructure variables

Variable	Default	Description
POSTGRES_HOST	localhost	PostgreSQL host for chat storage
POSTGRES_PORT	5432	PostgreSQL port
POSTGRES_DB	rossum_agent	PostgreSQL database name
POSTGRES_USER	rossum	PostgreSQL user
POSTGRES_PASSWORD	rossum	PostgreSQL password
VALKEY_HOST	localhost	Valkey host for change tracking
VALKEY_PORT	6379	Valkey port
VALKEY_PASSWORD	—	Valkey authentication password
SLACK_BOT_TOKEN	—	Slack bot token for report integration
SLACK_CHANNEL	—	Slack channel for posting reports

Usage

REST API

# Development (uvicorn)
rossum-agent-api --host 0.0.0.0 --port 8000 --reload

# Production (gunicorn)
rossum-agent-api --server gunicorn --host 0.0.0.0 --port 8000 --workers 4

Option	Description
--server	Backend: uvicorn (default) or gunicorn
--host	Host to bind to (default: 127.0.0.1)
--port	Port to listen on (default: 8000)
--workers	Number of worker processes (default: 1)
--reload	Enable auto-reload (uvicorn only)

API docs available at /api/docs (Swagger) and /api/redoc.

Python SDK

import asyncio
from rossum_agent.agent import create_agent
from rossum_agent.rossum_mcp_integration.connection import connect_mcp_server

async def main():
    mcp_connection = await create_mcp_connection()
    agent = await create_agent(mcp_connection=mcp_connection)

    async for step in agent.run("List all queues"):
        if step.final_answer:
            print(step.final_answer)

asyncio.run(main())

Available Tools

The agent provides internal tools and access to 30 MCP tools via dynamic loading.

Internal tools

Category	Tools
File & Memory	write_file · search_knowledge_base · search_elis_docs
Data	run_jq · run_grep
Execution	execute_python
Schema	patch_schema_with_subagent
Skills	load_skill
Document Testing	generate_mock_pdf
Task Tracking	create_task · update_task · list_tasks
User Interaction	ask_user_question

Dynamic MCP tool loading

Tools are loaded on-demand to reduce context usage. Categories are auto-loaded based on keywords in the user's message:

Category	Description
annotations	Upload, retrieve, update, confirm documents
queues	Create, configure, list queues
schemas	Define, modify field structures
engines	Extraction and splitting engines
hooks	Extensions and webhooks
email_templates	Automated email responses
document_relations	Export/einvoice links
relations	Annotation relations
rules	Schema validation rules
users	User and role management
workspaces	Workspace management

REST API Endpoints

Endpoint	Description
GET /api/v1/health	Health check
POST /api/v1/chats	Create new chat
GET /api/v1/chats	List all chats
GET /api/v1/chats/{id}	Get chat details
DELETE /api/v1/chats/{id}	Delete chat
POST /api/v1/chats/{id}/messages	Send message (streaming)
PUT /api/v1/chats/{id}/feedback	Submit feedback for a turn
GET /api/v1/chats/{id}/feedback	Get all feedback for a chat
DELETE /api/v1/chats/{id}/feedback/{turn}	Remove feedback
GET /api/v1/chats/{id}/files	List files
GET /api/v1/chats/{id}/files/{name}	Download file
GET /api/v1/commands	List available slash commands

Streaming uses AI SDK UI Message Stream v1 (x-vercel-ai-ui-message-stream: v1). MCP mode and persona can be set at chat creation or overridden per message.

License

MIT License - see LICENSE for details.

Resources

• Full Documentation
• API Reference
• MCP Server README
• Rossum API Documentation
• Main Repository