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by ivossos

FCCS MCP Agentic Server

Oracle EPM Cloud Financial Consolidation and Close (FCCS) agentic server using Google ADK with MCP support.

Features

  • 25+ FCCS Tools: Full coverage of Oracle FCCS REST API

  • Dual Mode: MCP server (Claude Desktop) + Web API (FastAPI)

  • Memory & Feedback: PostgreSQL persistence with RL tracking

  • Mock Mode: Development without real FCCS connection

  • Bilingual: English and Portuguese support

Quick Start

Automated Setup:

.\setup-windows.bat

This will:

  • Create virtual environment

  • Install all dependencies

  • Create .env file from template

  • Guide you through configuration

Manual Setup:

  1. Create virtual environment: python -m venv venv

  2. Activate: .\venv\Scripts\Activate.ps1

  3. Install: pip install -e .

  4. Configure: Copy .env.example to .env and edit

  5. Initialize database: python scripts\init_db.py (if using PostgreSQL)

Quick Commands:

  • Start web server: .\start-server.bat

  • Start MCP server: .\start-mcp-server.bat

  • Install dependencies: .\install-dependencies.bat

  • Initialize database: .\init-database.bat

See WINDOWS_DEPLOYMENT.md for detailed Windows setup guide.

Linux/Mac

1. Install Dependencies:

pip install -e .

2. Configure Environment:

cp .env.example .env # Edit .env with your settings

3. Run:

MCP Server (for Claude Desktop):

python -m cli.mcp_server

Web Server (for API access):

python -m web.server

Interactive CLI:

python -m cli.main

Claude Desktop Configuration

Add to %APPDATA%\Claude\claude_desktop_config.json:

{ "mcpServers": { "fccs-agent": { "command": "python", "args": ["-m", "cli.mcp_server"], "cwd": "C:\\path\\to\\fccs-mcp-ag-server", "env": { "FCCS_MOCK_MODE": "true" } } } }

API Endpoints

Endpoint

Method

Description

/

GET

Health check

/tools

GET

List available tools

/execute

POST

Execute a tool

/tools/{name}

POST

Call specific tool

/feedback

POST

Submit user feedback

/metrics

GET

Get tool metrics

Available Tools

Application

  • get_application_info - FCCS application details

  • get_rest_api_version - API version info

Jobs

  • list_jobs - List recent jobs

  • get_job_status - Job status by ID

  • run_business_rule - Execute business rules

  • run_data_rule - Execute data load rules

Dimensions

  • get_dimensions - List all dimensions

  • get_members - Get dimension members

  • get_dimension_hierarchy - Build hierarchy tree

Journals

  • get_journals - List journals

  • get_journal_details - Journal details

  • perform_journal_action - Approve, reject, post

  • update_journal_period - Update period

  • export_journals / import_journals

Data

  • export_data_slice - Export grid data

  • smart_retrieve - Smart data retrieval

  • copy_data / clear_data

Reports

  • generate_report - Generate FCCS reports

  • get_report_job_status - Async report status

Consolidation

  • export_consolidation_rulesets / import_consolidation_rulesets

  • validate_metadata

  • generate_intercompany_matching_report

  • import_supplementation_data

  • deploy_form_template

Architecture

fccs-mcp-ag-server/ ├── fccs_agent/ # Main package │ ├── agent.py # Agent orchestration │ ├── config.py # Configuration │ ├── client/ # FCCS HTTP client │ ├── tools/ # 25+ tool modules │ └── services/ # Feedback service ├── cli/ # CLI & MCP server │ ├── main.py # Interactive CLI │ └── mcp_server.py # MCP stdio server └── web/ # FastAPI server └── server.py

Deployment

Windows

See WINDOWS_DEPLOYMENT.md for complete Windows deployment guide including:

  • Prerequisites installation

  • Automated setup scripts

  • Windows Service configuration

  • Troubleshooting

Docker

docker build -t fccs-agent . docker run -p 8080:8080 --env-file .env fccs-agent

Google Cloud Run

gcloud run deploy fccs-agent \ --source . \ --region us-central1 \ --allow-unauthenticated \ --set-env-vars FCCS_MOCK_MODE=true

See QUICK_DEPLOY.md for detailed Cloud Run deployment.

Feedback System

The agent tracks tool executions for reinforcement learning:

  • Automatic: Execution time, success/failure, errors

  • User Feedback: 1-5 rating via /feedback endpoint

  • Metrics: Aggregated stats via /metrics endpoint

Documentation

License

MIT

fccs-mcp-ag-server

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