Rossum MCP Server Documentation

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Welcome to Rossum MCP Server

AI-powered Rossum orchestration: Document workflows conversationally, debug pipelines automatically, and configure automation through natural language.

A Model Context Protocol (MCP) server and AI agent toolkit for the Rossum intelligent document processing platform. Transforms complex workflow setup, debugging, and configuration into natural language conversations.

Built with Python and the official rossum-sdk.

Vision & Roadmap

This project enables three progressive levels of AI-powered Rossum orchestration:

  1. 📝 Workflow Documentation (Current Focus) - Conversationally document Rossum setups, analyze existing workflows, and generate comprehensive configuration reports through natural language prompts

  2. 🔍 Automated Debugging (In Progress) - Automatically diagnose pipeline issues, identify misconfigured hooks, detect schema problems, and suggest fixes through intelligent analysis

  3. 🤖 Agentic Configuration (Planned) - Fully autonomous setup and optimization of Rossum workflows - from queue creation to engine training to hook deployment - guided only by high-level business requirements

Features

The MCP server provides 40 tools organized into seven categories:

Document Processing

  • upload_document - Upload documents for AI extraction

  • get_annotation - Retrieve extracted data and status

  • list_annotations - List all annotations with filtering

  • start_annotation - Start annotation for field updates

  • bulk_update_annotation_fields - Update field values with JSON Patch

  • confirm_annotation - Confirm and finalize annotations

Queue & Schema Management

  • get_queue, get_schema, get_queue_schema - Retrieve configuration

  • get_queue_engine - Get engine information

  • create_queue, create_schema - Create new queues and schemas

  • update_queue, update_schema - Configure automation thresholds

  • patch_schema - Add, update, or remove individual schema nodes

Workspace Management

  • get_workspace - Retrieve workspace details by ID

  • list_workspaces - List all workspaces with optional filtering

  • create_workspace - Create a new workspace

User Management

  • get_user - Retrieve user details by ID

  • list_users - List users with filtering (for finding user URLs for token_owner)

  • list_user_roles - List all user roles (permission groups) in the organization

Engine Management

  • get_engine - Retrieve a single engine by ID

  • list_engines - List all engines with optional filters

  • create_engine - Create extraction or splitting engines

  • update_engine - Configure learning and training queues

  • create_engine_field - Define engine fields and link to schemas

  • get_engine_fields - Retrieve engine fields for a specific engine or all fields

Extensions & Rules

  • get_hook - Get hook/extension details

  • list_hooks - List webhooks and extensions

  • create_hook - Create webhooks or serverless function hooks

  • update_hook - Update hook properties (name, queues, events, config, settings, active)

  • list_hook_templates - List available hook templates from Rossum Store

  • create_hook_from_template - Create hooks from pre-built templates

  • list_hook_logs - List hook execution logs for debugging and monitoring

  • get_rule - Get business rule details

  • list_rules - List business rules with trigger conditions and actions

Relations Management

  • get_relation - Retrieve relation details by ID

  • list_relations - List all relations between annotations (edit, attachment, duplicate)

  • get_document_relation - Retrieve document relation details by ID

  • list_document_relations - List all document relations (export, einvoice)

Deployment Toolkit

The rossum_deploy package provides configuration deployment:

  • Pull configurations from Rossum organizations to local files

  • Diff local vs remote configurations

  • Push changes back to Rossum (with dry-run support)

  • Cross-organization deployment with ID mapping

  • Workspace comparison for safe agent workflows

AI Agent Toolkit

The rossum_agent package provides additional capabilities:

  • Knowledge Base search for Rossum documentation with Opus-powered analysis

  • Hook debugging tools with sandboxed code execution and Opus sub-agent analysis

  • Deployment tools for pull/push/diff of Rossum configurations across environments

  • Multi-environment support with spawnable MCP connections

  • Skills system for domain-specific workflows (deployment, hook debugging)

  • File output for saving reports, documentation, and analysis results

  • Integration with AI agent frameworks (Anthropic Claude via AWS Bedrock)

  • Streamlit web UI and REST API interfaces

  • See the Examples section for complete workflows

Deployment Tools

The rossum_deploy package provides lightweight deployment capabilities:

  • Pull/diff/push workflow for Rossum configurations

  • Support for Workspace, Queue, Schema, Hook, and Inbox objects

  • Conflict detection when both local and remote have changed

  • Python-first API designed for agent integration

  • Lightweight alternative to deployment-manager (PRD2)

Quick Start

Prerequisites: Python 3.12+, Rossum account with API credentials

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

# Install both packages with all features
uv sync --extra all --no-install-project

# Set up environment variables
export ROSSUM_API_TOKEN="your-api-token"
export ROSSUM_API_BASE_URL="https://api.elis.rossum.ai/v1"
export ROSSUM_MCP_MODE="read-write"  # Optional: "read-only" or "read-write" (default)

Run the MCP server:

rossum-mcp

Run the AI agent:

# CLI interface
rossum-agent

# Streamlit web UI
streamlit run rossum-agent/rossum_agent/app.py

# Or run with Docker Compose
docker-compose up rossum-agent

For detailed installation options, see Installation

Indices and tables