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Momosasu

omnifabric-mcp

by Momosasu

omnifabric-mcp

MCP server giving an LLM SQL access to a CloudSigma OmniFabric database (MatrixOne-compatible, MySQL wire protocol).

What It Does

Exposes one MCP tool, run_query, that runs any SQL statement against your OmniFabric/MatrixOne instance over the standard MySQL wire protocol (via mysql2) and returns the rows as JSON. No schema-specific tooling, no query rewriting — whatever SQL you (or the LLM) send is what runs.

Related MCP server: mcp-mysql-explorer

Prerequisites

  • Node.js 20.6+ (uses the native --env-file flag for local testing)

  • A running OmniFabric instance and its connection details: host, port (default 6001), account UUID, username, role, password

  • An MCP-compatible client (Claude Code, Claude Desktop, etc.)

Why a custom server instead of an existing one

  • Memoria (matrixorigin/Memoria) is a semantic-memory product built on MatrixOne (store/retrieve/branch/merge memories), not a raw SQL passthrough tool — doesn't fit.

  • mcp-server-mysql (generic community MySQL MCP server) looked like a fit but has two bugs for this use case: it hard-rejects any statement its SQL parser doesn't classify as SELECT (so SHOW DATABASES — the exact acceptance-test query — gets rejected), and it wraps every query in SET SESSION TRANSACTION READ ONLY, which isn't confirmed to work on MatrixOne/OmniFabric.

  • So: this repo, built directly on mysql2 + @modelcontextprotocol/sdk (both do the heavy lifting — no custom wire protocol). One tool, run_query, passes SQL straight through.

Safety model

There is no app-level statement filtering (that's what broke the alternative above). Instead: connect with a read-only DB role. Ask CloudSigma/whoever provisioned the instance for a role scoped to SELECT only, or check whether OmniFabric supports creating one beyond accountadmin. Only point this server at a write-capable role if you actually need DDL/write access.

Quick install via AI agent

Give this prompt to Claude Code (or any AI coding agent with shell access):

Install the OmniFabric MCP server. Clone https://github.com/Momosasu/omnifabric-mcp.git, run npm install, copy .env.example to .env and ask me for my OmniFabric credentials (host, account UUID, username, role, password) to fill it in, add it to my MCP config at ~/.claude/.mcp.json with args set to ["--env-file=<absolute path to .env>", "<absolute path to index.js>"], and verify the connection by calling run_query with SHOW DATABASES.

Quick Start

1. Install

git clone https://github.com/Momosasu/omnifabric-mcp.git
cd omnifabric-mcp
npm install

2. Configure credentials

cp .env.example .env

Fill in .env with the credentials from your OmniFabric provisioning (CloudSigma console or mo_ctl deploy output):

OMNIFABRIC_HOST=your-instance.omni.example.cloudsigma.com
OMNIFABRIC_PORT=6001
OMNIFABRIC_ACCOUNT=your-account-uuid
OMNIFABRIC_USER=your-username
OMNIFABRIC_ROLE=your-role
OMNIFABRIC_PASSWORD=your-password

Optional: sanity-check the login works before touching MCP at all:

mysql -h <OMNIFABRIC_HOST> -P 6001 -u <ACCOUNT>:<USER>:<ROLE> -p

Then validate your .env assembles into a well-formed config (no live DB connection made):

npm test

3. Add to Claude Code

Add to your MCP config (~/.claude/.mcp.json or project .mcp.json), pointing at the .env you just filled in — no need to re-enter credentials here:

{
  "mcpServers": {
    "omnifabric": {
      "command": "node",
      "args": ["--env-file=/path/to/omnifabric-mcp/.env", "/path/to/omnifabric-mcp/index.js"]
    }
  }
}

Replace /path/to/omnifabric-mcp with your actual path.

4. Verify

Ask Claude: "Use run_query to run SHOW DATABASES"

Tools

  • run_query(sql) — runs any SQL statement, returns rows as JSON.

That's it. No create_snapshot/restore_snapshot/UDF tools yet — the PRD explicitly says not to add those speculatively. Add a wrapper tool once there's a concrete use case for a specific OmniFabric SQL-Reference statement raw passthrough doesn't cover well.

Available Tools

1 tool
run_queryA

Run a SQL statement against the OmniFabric database and return the results. Safety is enforced by the DB user's role/grants, not by this tool — use a read-only account unless writes are explicitly needed.

ParametersJSON Schema
NameRequiredDescriptionDefault
sqlYesSQL statement to execute

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that safety is enforced by DB user roles/grants, not the tool, which is useful. However, it omits details like error handling, return format, or potential side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences that are direct and efficient. Every sentence adds value with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one parameter and no output schema, the description covers purpose and critical safety advice. It could be enhanced by specifying that results are returned in a structured format, but it is adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already describes the 'sql' parameter. The description repeats 'SQL statement' without adding new meaning. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool runs a SQL statement against the OmniFabric database and returns results. The verb 'run' and resource 'SQL statement' are specific, and no sibling tools are present for differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides guidance on safety by recommending a read-only account unless writes are explicitly needed. It does not specify when not to use the tool or list alternatives, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool updatev1.0.0
    • First observedrun_query

TDQS

A3.9/5.0
Disambiguation5/5

Only one tool exists, so there is no possibility of ambiguity between tools.

Naming Consistency5/5

With a single tool, naming conventions are trivially consistent.

Tool Count2/5

A single SQL query tool is too few for a database server; agents would likely need schema exploration or metadata tools.

Completeness2/5

The server lacks essential tools for database interaction, such as listing tables or describing schemas, making it severely incomplete.

Maintenance

ActivityStale
ResponsivenessSyncing

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

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