Ofrag

krokozyab16stars

MCP server and agentic SQL/RAG engine for Oracle Fusion metadata and live queries

Knowledge Memory Cloud Infrastructure Databases

1# Ofrag

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Last checked: 2026-10-28

Stars: 16
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Ofrag?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Ofrag need an API key?

No required environment variable is listed on this record.

What transport does Ofrag use?

Ofrag runs locally over stdio.

When was Ofrag last checked?

Last checked 2026-10-28. MCP server and agentic SQL/RAG engine for Oracle Fusion metadata and live queries

From the publisher

Documentation

The Problem

Oracle Fusion Cloud has 25,000+ tables across Finance, SCM, HCM, and Procurement. Finding the right table, understanding join relationships, and writing correct SQL takes hours of digging through Oracle docs. Even experienced consultants spend 15+ minutes per query cycle: log into BI Publisher → create data model → write SQL → debug → re-run.

ofrag eliminates this entirely. Your AI agent discovers tables semantically, validates SQL against a local schema cache, and executes queries against live Fusion data — all in one conversation.

✨ The Magic Moment

You: "Show me the top 5 unpaid invoices for vendor Acme Corp generated last month."

Claude + ofrag:

Discovers the right tables via semantic search (AP_INVOICES_ALL, POZ_SUPPLIERS, HZ_PARTIES)

Understands "unpaid" means PAYMENT_STATUS_FLAG = 'N'

Validates the SQL against local metadata — catches errors before they hit production

Executes the query against your live Oracle Fusion instance

Returns a formatted table with invoice numbers, amounts, and dates

Total time: ~4 seconds.

No BI Publisher. No data model. No OTBI subject areas. Just a question and an answer.

🧠 What is ofrag

ofrag is an MCP (Model Context Protocol) server — an open standard that lets AI agents use external tools. It gives Claude, OpenAI, Gemini, and any MCP-compatible LLM structured access to your Oracle Fusion Cloud data.

┌──────────────────────────────────────────────────────────────┐
│                      Your AI Agent                           │
│           Claude · OpenAI · Gemini · Claude Code             │
├──────────────────────────────────────────────────────────────┤
│                    ofrag (MCP Server)                        │
│                                                              │
│  ┌─────────────┐  ┌──────────────┐  ┌─────────────────────┐  │
│  │  Semantic   │  │  SQL Linter  │  │  Business Process   │  │
│  │  Search     │  │  (AST-based) │  │  Mapper             │  │
│  └──────┬──────┘  └──────┬───────┘  └──────────┬──────────┘  │
│         │                │                     │             │
│  ┌──────▼──────────────────────────────────────▼──────────┐  │
│  │           Local DuckDB Metadata Cache                  │  │
│  │          25,000+ tables · 240K+ descriptions           │  │
│  └────────────────────────┬───────────────────────────────┘  │
│                           │ Only validated queries           │
├───────────────────────────▼──────────────────────────────────┤
│                  Oracle Fusion Cloud                         │
│            BI Publisher SOAP · REST APIs                     │
└──────────────────────────────────────────────────────────────┘

Key principle: All schema exploration happens locally — zero queries to production during discovery. Only final, validated SQL reaches your live Fusion instance.

🔑 Why ofrag Has No Alternatives

	ofrag + AI Agent	Manual BI Publisher	OTBI	Proprietary SQL Tools
Natural language queries	✅ Ask in plain English	❌ Write SQL manually	❌ Drag-and-drop only	❌ Write SQL manually
Schema discovery	✅ Semantic search across 25K+ tables	❌ Read Oracle docs	❌ Limited subject areas	✅ Table browser
SQL validation before execution	✅ AST parsing against local cache	❌ Trial and error	N/A	❌
Cross-module table relationships	✅ AI traces AP→XLA→GL chains	❌ Manual knowledge	❌ Single subject area	❌
Business process mapping	✅ `business_process_map`, `scenario_mapper`	❌	❌	❌
Multi-environment switching	✅ DEV/SIT/UAT/PROD in one session	❌ Separate logins	❌ Separate logins	Partial
REST API access	✅ Built-in universal REST client	❌	❌	❌
Production safety	✅ Local-first, validated queries only	⚠️ Direct execution	✅ Sandboxed	⚠️ Direct execution

The real difference: Other tools help you write SQL. ofrag lets you skip writing SQL — the AI does it for you, correctly, using verified metadata.

🛠 Tool Catalog

ofrag exposes 30+ tools to your AI agent, organized by function:

Discovery & Search

Tool	What it does
`semantic_search`	Find tables/columns by business meaning ("unpaid invoices", "employee compensation") using vector embeddings across 240K+ descriptions
`search_identifiers`	Find tables/columns by Oracle name pattern (`AP_INVOICES`, `VENDOR_ID`)
`search_descriptions`	Exact keyword search in table/column descriptions
`list_tables`	Browse tables by module with filters
`list_columns`	Get all columns, types, and descriptions for a table
`index_info`	Index definitions for a table
`table_overview`	Quick summary: column count, purpose, module

SQL & Execution

Tool	What it does
`execute_oracle_sql`	Execute live SQL against Oracle Fusion, results inline
`execute_oracle_sql_to_file`	Execute SQL, save results to local file (for large datasets)
`lint_sql`	Parse SQL into AST, validate against cached schema — catches errors before execution
`suggest_sql`	Auto-complete partial SQL using metadata cache
`raw_select`	Query the local DuckDB metadata cache directly

Business Intelligence

Tool	What it does
`module_summary`	Overview of a Fusion module — purpose, key tables, typical queries
`business_process_map`	Map a business process to its tables, stages, and key columns
`scenario_mapper`	Map a business intent ("month-end close") to recommended tables and metrics
`relationship_map`	Show inbound/outbound JOIN relationships for any table
`cross_module_analyzer`	Analyze how a table connects across Fusion modules
`integration_flow_mapper`	Trace end-to-end data flow: upstream feeders → table → downstream consumers
`process_catalog`	Full business process catalog with all stages and tables

REST API

Tool	What it does
`rest_call`	Make HTTP REST API calls to Oracle Fusion, results inline
`rest_call_to_file`	REST API calls with results saved to file

Fusion Configuration

Tool	What it does
`describe_flexfield`	Describe Descriptive Flexfields (DFF) — contexts, segments, value sets
`lookup_values`	Get all values for a Fusion lookup type (LOV)
`profile_values`	Get profile option values at site/product/user levels

BI Publisher & ESS

Tool	What it does
`run_bi_report`	Execute a BI Publisher report with parameters, results inline
`run_bi_report_to_file`	Execute BI Publisher report, save output to file
`submit_ess_job`	Submit an ESS job (batch processes, imports, exports)
`get_ess_job_status`	Check ESS job status

Environment Management

Tool	What it does
`authenticate`	Browser-based SSO login to Oracle Fusion
`get_auth_status`	Check current authentication state
`add_environment`	Add/update a named environment (DEV, SIT, UAT, PROD)
`switch_environment`	Switch active environment instantly
`list_environments`	List all configured environments
`compare_environments`	Compare configuration data between two environments

🚀 Quick Start

1. Get the binary

Download from Releases (Windows and macOS).

2. Follow the setup guide

👉 Installation & Setup Guide — step-by-step: licensing, BI Publisher report deployment, MCP client configuration (Claude Desktop, Gemini, Claude Code), authentication setup.

3. Start talking to your ERP

"What tables store AP invoice data?"
"Show me all overdue invoices for Acme Corp"
"How are accounts payable balances linked to the general ledger?"
"Compare the supplier count between DEV and PROD"

💡 Use Cases

Ad-hoc data analysis — Ask "show me revenue by business unit for Q4" and get results in seconds. No OTBI report creation, no BI Publisher data model, no waiting.

Implementation troubleshooting — During Fusion implementation, quickly verify data: "are there any AP invoices without distributions?", "show me GL journal entries that haven't been transferred from XLA".

Data reconciliation — "Compare AP subledger totals against GL balances for period DEC-24". The AI traces the full AP → XLA → GL chain and identifies discrepancies.

Schema exploration — "What tables store employee compensation data?" The AI uses semantic search to find relevant HCM tables, shows their relationships, and explains the data model.

Integration development — Building OIC integrations? Ask "what REST endpoints exist for AP invoices?" or "what's the FBDI template for importing journals?" — ofrag finds it.

EBS → Fusion migration — "What's the Fusion equivalent of AP_INVOICES_ALL in EBS?" The AI maps EBS tables to Fusion tables using semantic search and module knowledge.

Report development — Before building a BI Publisher report, prototype your SQL through conversation. The AI validates and optimizes your queries using the local schema cache.

⚠️ Limitations

Read-only SQL — SELECT queries only through BI Publisher SOAP. Oracle Fusion does not permit write access through this layer.
Security — Ensure usage complies with your organization's security policies. Credentials are stored locally and never transmitted to third parties.

📄 Documentation

Guide	Description
Installation & Setup	Detailed guide on how to install, configure, and get the binary running
Full MCP Server Reference	Complete reference for configuration, authentication, variables and tools
Multi-Environment Management	Configure and switch between dev, UAT, prod environments interactively
Semantic Search Setup	How to enable vector search and REST API catalog for full-powered semantic discovery

🌐 Ecosystem

ofrag is part of the Oracle Fusion open-source ecosystem:

Project	What it does	Link
ofrag	MCP Server — AI-powered queries via Claude, OpenAI, Gemini	GitHub
OFJDBC	JDBC driver — SQL access from DBeaver, IntelliJ, JVM apps, ETL pipelines	GitHub

📫 Contact

Website: oraclefusionsql.com
GitHub Issues: krokozyab/ofrag/issues
Email: [email protected]
LinkedIn: Sergey Rudenko

Ofrag

krokozyab16stars

MCP server and agentic SQL/RAG engine for Oracle Fusion metadata and live queries

Knowledge Memory Cloud Infrastructure Databases

Install Run on PlugMCP

GitHub

Run on PlugMCP

1# Ofrag

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Last checked: 2026-10-28

Stars: 16
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Ofrag?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Ofrag need an API key?

No required environment variable is listed on this record.

What transport does Ofrag use?

Ofrag runs locally over stdio.

When was Ofrag last checked?

Last checked 2026-10-28. MCP server and agentic SQL/RAG engine for Oracle Fusion metadata and live queries

From the publisher

Documentation

The Problem

ofrag eliminates this entirely. Your AI agent discovers tables semantically, validates SQL against a local schema cache, and executes queries against live Fusion data — all in one conversation.

✨ The Magic Moment

You: "Show me the top 5 unpaid invoices for vendor Acme Corp generated last month."

Claude + ofrag:

Discovers the right tables via semantic search (AP_INVOICES_ALL, POZ_SUPPLIERS, HZ_PARTIES)

Understands "unpaid" means PAYMENT_STATUS_FLAG = 'N'

Validates the SQL against local metadata — catches errors before they hit production

Executes the query against your live Oracle Fusion instance

Returns a formatted table with invoice numbers, amounts, and dates

Total time: ~4 seconds.

No BI Publisher. No data model. No OTBI subject areas. Just a question and an answer.

🧠 What is ofrag

┌──────────────────────────────────────────────────────────────┐
│                      Your AI Agent                           │
│           Claude · OpenAI · Gemini · Claude Code             │
├──────────────────────────────────────────────────────────────┤
│                    ofrag (MCP Server)                        │
│                                                              │
│  ┌─────────────┐  ┌──────────────┐  ┌─────────────────────┐  │
│  │  Semantic   │  │  SQL Linter  │  │  Business Process   │  │
│  │  Search     │  │  (AST-based) │  │  Mapper             │  │
│  └──────┬──────┘  └──────┬───────┘  └──────────┬──────────┘  │
│         │                │                     │             │
│  ┌──────▼──────────────────────────────────────▼──────────┐  │
│  │           Local DuckDB Metadata Cache                  │  │
│  │          25,000+ tables · 240K+ descriptions           │  │
│  └────────────────────────┬───────────────────────────────┘  │
│                           │ Only validated queries           │
├───────────────────────────▼──────────────────────────────────┤
│                  Oracle Fusion Cloud                         │
│            BI Publisher SOAP · REST APIs                     │
└──────────────────────────────────────────────────────────────┘

Key principle: All schema exploration happens locally — zero queries to production during discovery. Only final, validated SQL reaches your live Fusion instance.

🔑 Why ofrag Has No Alternatives

	ofrag + AI Agent	Manual BI Publisher	OTBI	Proprietary SQL Tools
Natural language queries	✅ Ask in plain English	❌ Write SQL manually	❌ Drag-and-drop only	❌ Write SQL manually
Schema discovery	✅ Semantic search across 25K+ tables	❌ Read Oracle docs	❌ Limited subject areas	✅ Table browser
SQL validation before execution	✅ AST parsing against local cache	❌ Trial and error	N/A	❌
Cross-module table relationships	✅ AI traces AP→XLA→GL chains	❌ Manual knowledge	❌ Single subject area	❌
Business process mapping	✅ `business_process_map`, `scenario_mapper`	❌	❌	❌
Multi-environment switching	✅ DEV/SIT/UAT/PROD in one session	❌ Separate logins	❌ Separate logins	Partial
REST API access	✅ Built-in universal REST client	❌	❌	❌
Production safety	✅ Local-first, validated queries only	⚠️ Direct execution	✅ Sandboxed	⚠️ Direct execution

The real difference: Other tools help you write SQL. ofrag lets you skip writing SQL — the AI does it for you, correctly, using verified metadata.

🛠 Tool Catalog

ofrag exposes 30+ tools to your AI agent, organized by function:

Discovery & Search

Tool	What it does
`semantic_search`	Find tables/columns by business meaning ("unpaid invoices", "employee compensation") using vector embeddings across 240K+ descriptions
`search_identifiers`	Find tables/columns by Oracle name pattern (`AP_INVOICES`, `VENDOR_ID`)
`search_descriptions`	Exact keyword search in table/column descriptions
`list_tables`	Browse tables by module with filters
`list_columns`	Get all columns, types, and descriptions for a table
`index_info`	Index definitions for a table
`table_overview`	Quick summary: column count, purpose, module

SQL & Execution

Tool	What it does
`execute_oracle_sql`	Execute live SQL against Oracle Fusion, results inline
`execute_oracle_sql_to_file`	Execute SQL, save results to local file (for large datasets)
`lint_sql`	Parse SQL into AST, validate against cached schema — catches errors before execution
`suggest_sql`	Auto-complete partial SQL using metadata cache
`raw_select`	Query the local DuckDB metadata cache directly

Business Intelligence

Tool	What it does
`module_summary`	Overview of a Fusion module — purpose, key tables, typical queries
`business_process_map`	Map a business process to its tables, stages, and key columns
`scenario_mapper`	Map a business intent ("month-end close") to recommended tables and metrics
`relationship_map`	Show inbound/outbound JOIN relationships for any table
`cross_module_analyzer`	Analyze how a table connects across Fusion modules
`integration_flow_mapper`	Trace end-to-end data flow: upstream feeders → table → downstream consumers
`process_catalog`	Full business process catalog with all stages and tables

REST API

Tool	What it does
`rest_call`	Make HTTP REST API calls to Oracle Fusion, results inline
`rest_call_to_file`	REST API calls with results saved to file

Fusion Configuration

Tool	What it does
`describe_flexfield`	Describe Descriptive Flexfields (DFF) — contexts, segments, value sets
`lookup_values`	Get all values for a Fusion lookup type (LOV)
`profile_values`	Get profile option values at site/product/user levels

BI Publisher & ESS

Tool	What it does
`run_bi_report`	Execute a BI Publisher report with parameters, results inline
`run_bi_report_to_file`	Execute BI Publisher report, save output to file
`submit_ess_job`	Submit an ESS job (batch processes, imports, exports)
`get_ess_job_status`	Check ESS job status

Environment Management

Tool	What it does
`authenticate`	Browser-based SSO login to Oracle Fusion
`get_auth_status`	Check current authentication state
`add_environment`	Add/update a named environment (DEV, SIT, UAT, PROD)
`switch_environment`	Switch active environment instantly
`list_environments`	List all configured environments
`compare_environments`	Compare configuration data between two environments

🚀 Quick Start

1. Get the binary

Download from Releases (Windows and macOS).

2. Follow the setup guide

👉 Installation & Setup Guide — step-by-step: licensing, BI Publisher report deployment, MCP client configuration (Claude Desktop, Gemini, Claude Code), authentication setup.

3. Start talking to your ERP

"What tables store AP invoice data?"
"Show me all overdue invoices for Acme Corp"
"How are accounts payable balances linked to the general ledger?"
"Compare the supplier count between DEV and PROD"

💡 Use Cases

Ad-hoc data analysis — Ask "show me revenue by business unit for Q4" and get results in seconds. No OTBI report creation, no BI Publisher data model, no waiting.

Data reconciliation — "Compare AP subledger totals against GL balances for period DEC-24". The AI traces the full AP → XLA → GL chain and identifies discrepancies.

Schema exploration — "What tables store employee compensation data?" The AI uses semantic search to find relevant HCM tables, shows their relationships, and explains the data model.

Integration development — Building OIC integrations? Ask "what REST endpoints exist for AP invoices?" or "what's the FBDI template for importing journals?" — ofrag finds it.

EBS → Fusion migration — "What's the Fusion equivalent of AP_INVOICES_ALL in EBS?" The AI maps EBS tables to Fusion tables using semantic search and module knowledge.

Report development — Before building a BI Publisher report, prototype your SQL through conversation. The AI validates and optimizes your queries using the local schema cache.

⚠️ Limitations

Read-only SQL — SELECT queries only through BI Publisher SOAP. Oracle Fusion does not permit write access through this layer.
Security — Ensure usage complies with your organization's security policies. Credentials are stored locally and never transmitted to third parties.

📄 Documentation

Guide	Description
Installation & Setup	Detailed guide on how to install, configure, and get the binary running
Full MCP Server Reference	Complete reference for configuration, authentication, variables and tools
Multi-Environment Management	Configure and switch between dev, UAT, prod environments interactively
Semantic Search Setup	How to enable vector search and REST API catalog for full-powered semantic discovery

🌐 Ecosystem

ofrag is part of the Oracle Fusion open-source ecosystem:

Project	What it does	Link
ofrag	MCP Server — AI-powered queries via Claude, OpenAI, Gemini	GitHub
OFJDBC	JDBC driver — SQL access from DBeaver, IntelliJ, JVM apps, ETL pipelines	GitHub

📫 Contact

Website: oraclefusionsql.com
GitHub Issues: krokozyab/ofrag/issues
Email: [email protected]
LinkedIn: Sergey Rudenko