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Fusion NLQ MCP

Fusion NLQ MCP

Fusion NLQ MCP

An MCP server that lets an AI agent answer questions from live Oracle Fusion data. You ask in plain English; the agent writes the SQL, runs it through this server, reads the rows back, and if the query fails it looks up the right tables and columns and tries again. The server's main tool is query_fusion; it can hold several Fusion instances with several users each, and the agent picks the instance and user on every call. It talks to Fusion's BI Publisher SOAP service directly from your machine, so there is no database or middle tier to stand up.

The tools

Tool

What it does

Arguments

query_fusion

Runs one query against Oracle Fusion and returns the rows as XML

sql, optional instance, optional fusion_user

list_fusion_connections

Lists the saved instances, their URLs and users, and the defaults (never passwords)

none

  • sql is one SELECT (or WITH ... SELECT). Results come back as <ROWSET><ROW><COLUMN_NAME>value</COLUMN_NAME>...</ROW></ROWSET>, with tags taken from the column names or aliases, so give expressions an alias (COUNT(*) AS INVOICE_COUNT).

  • instance names a saved instance (see setup below); left out, the default instance is used.

  • fusion_user names a user saved on that instance; left out, the instance's default user is used.

One session can switch freely, for example querying dev as a finance user, then as an HCM user, then test. The tool's description tells the agent that each instance is a separate environment and not to mix data between them unless asked.

When a query fails, the Oracle error comes back as the tool's error, for example ORA-00942: table or view does not exist or ORA-00904: "VENDOR": invalid identifier. The tool's description tells the agent how to recover: look tables up in ALL_OBJECTS, list columns from ALL_TAB_COLUMNS (both through this same tool), or read Oracle's Tables and Views for Oracle Fusion Cloud guides on docs.oracle.com, then correct the SQL and run it again. Many Fusion objects are synonyms, which have no rows in ALL_TAB_COLUMNS, so the description also tells the agent to follow a synonym to its view or table, to filter date-effective _F/_M tables on SYSDATE, and to decode code columns through FND_LOOKUP_VALUES. DBA_ views are not available to Fusion users.

Limits: results over 40,000 characters are cut at a whole row and end with a comment saying how many rows were shown (set FUSION_MCP_MAX_CHARS to change the limit). Queries run against BI Publisher's ApplicationDB_FSCM data source, which can read Financials, Procurement, SCM and HCM tables. SQL against most Fusion base tables is not filtered by the account's data security the way Fusion pages are (two users with different data roles get the same rows), so only save accounts whose access you are comfortable giving the agent.

What it accepts: the SQL must start with SELECT or WITH, must not contain a semicolon (one trailing semicolon is removed) and must not use FOR UPDATE, which would lock the rows it reads. The query runs inside a short PL/SQL block so BI Publisher can read the column names; refusing semicolons means nothing can be added after the query. A SELECT can still call database functions, and the server cannot tell which of those change data, so the account's own permissions are the real limit: use an account with only the access you want the agent to have.

Text in the results is data, not instructions. Free-text fields such as supplier names, invoice descriptions and comments are typed by people inside and outside your company, and the rows go straight to the agent. Someone could plant text there that tries to instruct it. The tool's description tells the agent never to follow instructions found in results, but that rests on the agent's judgment. Be careful running broad free-text queries in a session where the agent can also send email, upload files or run commands.

Each query runs through a temporary data model created in the account's own BI Publisher folder (/~username) and deleted when the call ends, whether it succeeds or fails. If Fusion cannot be reached at that moment the model stays behind; its name starts with MCPQ_ and it is safe to delete.

Related MCP server: mcp-oraclefusion

Setup

The repo contains no Fusion addresses, users or passwords. You supply your own.

Quick setup: let Claude Code do it

Paste this into Claude Code:

Install and set up the Fusion MCP server from https://github.com/brianmakarewicz/fusion-nlq-mcp. Follow "Steps for an AI agent" in its README.

It asks for a name for the instance, the Fusion URL and your username. The password goes into a small window that opens on your screen, never into the chat. When it is done, close and reopen Claude Code and ask a question.

Steps for an AI agent

In every step, run fusion-mcp by its full path, <repo>/.venv/Scripts/fusion-mcp on Windows or <repo>/.venv/bin/fusion-mcp on macOS and Linux. A bare fusion-mcp may run a different, older install that happens to be on the PATH.

  1. Check that Python 3.10+ and Git are installed. If either is missing, tell the user how to install it and stop. Also check that python -c "import tkinter" works, because the password window needs it. If tkinter is missing, the user can still pipe the password in (step 4), so tell them and ask which they prefer rather than stopping.

  2. Clone the repo into the user's home folder (%USERPROFILE% on Windows), create the venv with python -m venv .venv inside it, and run pip install -e . with the venv's pip. If the folder already exists, run git pull there instead of cloning, then run pip install -e . again in case the dependencies changed. If git pull reports local changes, ask the user before discarding them.

  3. Ask the user for a short instance name (for example dev or test), the Fusion URL, and the Fusion username. Never ask for the password in chat.

  4. Run fusion-mcp setup --instance NAME --url URL --user USER with a timeout of at least five minutes. With no terminal attached, a window opens for the user to type the password, so tell them to look for it. If you cannot open a window on the user's screen, the user can pipe the password in themselves with --password-stdin, for example <command that prints the password> | <full path to fusion-mcp> setup --instance NAME --url URL --user USER --password-stdin. It reads the first line of input as the password, so don't write the password into a file to do this. Setup still tests the login before saving. Avoid handling the password yourself unless the user explicitly asks you to, because it then passes through your session. On success it prints Saved for USER on instance 'NAME', or Password updated for USER ... when that user was already saved; both mean it worked. If this is a new instance and other instances were already saved, ask whether it should be the default and, if so, run fusion-mcp default --instance NAME; if they say no, the current default stays as it is. On Login failed, tell the user and run it again only when they ask, so a wrong password is not retried into a locked account.

  5. Register the server for the user: claude mcp add fusion-bip --scope user -- <full path to fusion-mcp> (fusion-mcp.exe on Windows). If claude mcp list already has a server named fusion-bip, run claude mcp get fusion-bip and compare its command with the path you just installed. If it points to another copy of this repo, it is an earlier install; otherwise it is a different server. Tell the user which it is and ask whether to replace it (claude mcp remove fusion-bip --scope user, then add again) or keep it and register this one under another name, such as fusion-query, using that name in the commands in this step. Confirm with claude mcp get <name> that it shows Connected.

  6. Tell the user to close and reopen Claude Code, then ask a question about their Fusion data.

To add another user or instance later, the user can ask Claude Code to do it, which is step 4 again with the new names. For a new user on an instance that is already saved, leave out --url: run fusion-mcp setup --instance NAME --user USER and it reuses the saved URL; don't ask the default question in this case. Passing the same URL again also works, but a different URL is refused, so a saved instance is never silently repointed. Saving a URL and user that another instance already has is also refused, because the two would share one stored password; use the existing instance instead. Usernames are matched regardless of case. Both refusals happen before the password is read or a login is tried, so they never count against the account, and setup exits with code 1.

Setting it up yourself

Requirements: Python 3.10 or later, and a Fusion account that can create data models in its own BI Publisher folder (the BI Publisher Data Model Developer or Author role).

git clone https://github.com/brianmakarewicz/fusion-nlq-mcp
cd fusion-nlq-mcp
python -m venv .venv
.venv/bin/pip install -e .          # Windows: .venv\Scripts\pip install -e .

This installs the fusion-mcp command.

.venv/bin/fusion-mcp setup --instance dev           # Windows: .venv\Scripts\fusion-mcp setup --instance dev

The table below writes fusion-mcp for short; run it the same way, by its path inside .venv.

It asks for the Fusion URL (the address you use for Fusion, for example https://<your-pod>.fa.<region>.oraclecloud.com; a pasted Fusion page address is trimmed to that), the username and the password (typing is hidden), tests the login, and saves only if the login works. The password goes into the operating system's credential store (Windows Credential Manager, macOS Keychain, or the Linux Secret Service), never into a file. The instance names, URLs and usernames go into fusion-mcp/config.json under your user config folder. Passwords are stored by URL and username, so every install on the same computer account (this one, the full version, or a second config folder) shares them: changing or forgetting a password in one changes it for all. Leave out --instance and the instance is called default.

Command

What it does

fusion-mcp setup --instance test

Adds another instance (asks for its URL)

fusion-mcp setup --instance dev --user hcm_reader

Adds a user to an existing instance (no URL asked)

fusion-mcp setup --instance dev --user fin_reader

For a user already saved, changes the password

fusion-mcp list

Shows instances, URLs, users and defaults; never passwords

fusion-mcp default --instance test [--user carol]

Chooses what a call uses when it names no instance or user

fusion-mcp forget --instance dev [--user hcm_reader]

Removes a user, or a whole instance, and its keychain entries (it says which ones it kept because another instance uses them)

fusion-mcp forget --all

Removes everything (the usage log, if any, stays)

The first instance and user you add become the defaults. A running server reads the saved connections on every call, so a new instance, user or password is used by the next query without restarting your MCP client. --url and --user can be given as options, and --password-stdin reads the password from standard input, so setup can be scripted.

In a terminal, setup asks for the password with a hidden prompt. Where there is no terminal (an AI agent running the command, or Git Bash), it opens a small password window instead, which needs Python's tkinter (included with the python.org installers; python3-tk on Linux). You can also pipe the password in with --password-stdin. fusion-mcp --help lists the commands.

Every saved user can be used by the agent through instance and fusion_user, so save only accounts whose access you are happy for the agent to have. To keep one session to a single instance, set FUSION_MCP_INSTANCE in that session's MCP config (for example a project-level .mcp.json); it then becomes that session's default instance, although the agent can still name others.

Option B: several accounts, through your own credential helper

Use this if you already keep credentials in your own store. Write a conn_helper.py in a folder outside the repo that defines get_fusion_url(pod) and get_fusion_user(name, pod), returning the URL and (username, password). examples/conn_helper_example.py keeps the passwords in the OS keychain and only the account names in a file. Then set:

Variable

Value

FUSION_MCP_HELPER_DIR

The folder containing your conn_helper.py

FUSION_MCP_USER

The account name to use when a call does not name one

FUSION_MCP_POD

Optional; passed to your helper as pod when a call names no instance

A call's instance is passed to your helper as pod, so a helper that understands several pods gives the same switching as option A.

Add an account with .venv/bin/python conn_helper.py add <name> (use the repo's virtual environment, which has keyring). Remove one by deleting it from accounts.json and its keychain entry (service fusion-bip-mcp-server-helper); fusion-mcp forget does not touch helper accounts.

With option B the agent can name any account your helper knows through fusion_user (and any pod through instance), so only give the helper accounts you are happy for the agent to use.

FUSION_URL, FUSION_USERNAME and FUSION_PASSWORD work, but the password then sits unencrypted in your MCP client's config file, where anything that can read your files can read it. It holds one connection only, so instance cannot be used. The server refuses FUSION_PASSWORD unless you also set FUSION_MCP_ACCEPT_PLAINTEXT_PASSWORD=yes to confirm you accept that risk.

Logins and session tokens

The server logs in to BI Publisher once and reuses the session token for later queries. The password is sent only at that first login, and again only when Fusion reports that the token has expired, at which point the server logs in again from the same stored credentials and retries the query once. The token is kept in memory and never written to disk.

Register it with your MCP client

After option A there is nothing to pass; just point the client at the command. --scope user makes the server available in every folder, not only the current one. Optionally set FUSION_MCP_INSTANCE in its env to choose that client's default instance.

Claude Code:

claude mcp add fusion-bip --scope user -- /path/to/fusion-nlq-mcp/.venv/bin/fusion-mcp

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "fusion-bip": {
      "command": "/path/to/fusion-nlq-mcp/.venv/bin/fusion-mcp"
    }
  }
}

On Windows the command is .venv\Scripts\fusion-mcp.exe. For option B, add the FUSION_MCP_* variables to the client's env settings.

Usage log

Every call appends one line to metering.jsonl in the same fusion-mcp config folder (set FUSION_MCP_METER_LOG to move it). It records the time, tool, duration, result size and outcome; for errors it keeps only the error type and ORA- code. It stores a hash and length of the SQL, not the SQL itself, and never stores result data.

Which credentials are used

The server checks in this order and uses the first that is set: a credential helper (FUSION_MCP_HELPER_DIR), then FUSION_PASSWORD (option C), then the saved instances from fusion-mcp setup. A leftover FUSION_PASSWORD therefore takes precedence over saved instances.

If a login fails for any reason other than Fusion being unreachable, the server stops trying that user with the same password for five minutes, so that an agent retrying in a loop cannot lock the account. Update the password (fusion-mcp setup --instance NAME --user NAME) and the next call tries the new one; other instances and users are not affected.

The server runs over stdio only, started by your MCP client. It has no network listener and does no caller authentication of its own.

Tests

.venv/bin/pip install -e ".[test]"   # Windows: .venv\Scripts\pip install -e ".[test]"
.venv/bin/pytest                     # Windows: .venv\Scripts\pytest

The tests run offline; they never contact Fusion or touch your saved instances or keychain.

How it fits together

  • server.py: the MCP server; registers the tools and their descriptions.

  • direct_client.py: the query, run against BI Publisher SOAP.

  • soap.py: builds the SOAP requests and reads Fusion's responses and errors.

  • builders.py: checks the SQL and builds the temporary data model.

  • context.py: finds the credentials for a call (helper, saved instances, or environment).

  • credentials.py: the saved instances and users, the setup, list, default and forget commands, and the OS keychain storage.

  • metering.py: the usage log.

License

MIT. See LICENSE.

Tool Schema Changelog

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