cubrid-mcp-server
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A Model Context Protocol (MCP) server for CUBRID database — enabling LLMs to inspect schemas and execute read-only queries via pycubrid.
cubrid-mcp-server
A Model Context Protocol server for CUBRID, enabling LLMs to safely inspect schemas and execute read-only queries via pycubrid.
Features
| Tool | Description |
|---|---|
all_table_names |
List every user table in the database |
filter_table_names |
Substring search over table names |
schema_definitions |
Column types, nullability, defaults, and primary key info |
describe_table |
Full metadata: columns, primary key, and indexes in one call |
list_indexes |
Indexes for a table with key columns and flags |
explain_query |
Execution plan/trace for a SELECT/WITH (via CUBRID SHOW TRACE) |
table_row_counts |
COUNT(*) for one or many tables |
list_serials |
CUBRID SERIAL sequences with current value and bounds |
list_class_hierarchy |
CUBRID CLASS inheritance relationships |
execute_query |
Run read-only SQL with automatic output truncation |
health_check |
Verify database connectivity on demand |
execute_write |
Run a single INSERT/UPDATE/DELETE in an atomic transaction (only registered when opt-in write mode is enabled) |
Resources
Schema metadata is also exposed as read-only MCP Resources, so clients can discover and read schema context without a tool call. Resources reuse the same read-only catalog queries as the tools — no additional data access or write surface.
| Resource URI | Description |
|---|---|
cubrid://schema |
Whole-schema index: every user table with its per-table resource URI |
cubrid://schema/{table} |
Per-table metadata (columns, primary key, indexes) — mirrors describe_table |
Both return application/json. Table names in {table} are percent-decoded by URI-template matching; an unknown or system table produces a resource-read error, matching the describe_table tool.
Prompts
The server also exposes a small set of MCP Prompt templates — reusable, guided
starting points for common inspection tasks. Prompts are guidance-only: each one
returns text that tells the client which of the existing read-only tools to call and
in what order. They never touch the database, execute SQL, or add any new data-access
surface, and any argument you pass is fenced and treated strictly as untrusted data.
The prompts are advisory templates only — the actual read-only enforcement remains in
the underlying tools (execute_query/explain_query via safety.py).
| Prompt | Arguments | Description |
|---|---|---|
summarize_table |
table |
Describe a table, then sample it with a bounded read-only query |
explain_query |
sql |
Obtain and interpret a SELECT/WITH execution plan via explain_query |
inspect_schema |
(none) | Build a high-level overview of the whole schema from the read-only tools |
find_index_candidates |
table |
Review a table's index coverage for potential review areas |
Quick Start
Configure
Set the required environment variables:
export CUBRID_HOST=localhost
export CUBRID_PORT=33000 # optional, default: 33000
export CUBRID_USER=readonly_user # a CUBRID user with SELECT-only grants (see Security)
export CUBRID_PASSWORD=secret
export CUBRID_DATABASE=mydb
Optional settings:
| Variable | Default | Description |
|---|---|---|
CUBRID_MCP_READONLY |
1 |
Enforce read-only SQL whitelist |
CUBRID_MCP_MAX_CHARS |
4000 |
Max characters in query output |
CUBRID_MCP_MAX_ROWS |
1000 |
Max rows returned by execute_query before truncation |
CUBRID_MCP_MAX_SQL_LENGTH |
65536 |
Max length (characters) of a submitted SQL statement |
CUBRID_MCP_QUERY_TIMEOUT |
30 |
Per-statement socket read timeout in seconds. If the server sends no data within this window the query is aborted and the connection is reset. This is a socket read timeout, not a true server-side statement timeout. |
CUBRID_MCP_AUDIT_LOG |
0 |
Opt-in audit logging. When enabled, emits one redaction-safe JSON record per executed statement (execute_query/explain_query/execute_write) to stderr — see Logging. Honoured per connection (CUBRID_<NAME>_MCP_AUDIT_LOG). |
CUBRID_MCP_WRITE |
0 |
Opt-in write mode. When enabled (1), registers the execute_write tool for single-statement DML. Honoured per connection (CUBRID_<NAME>_MCP_WRITE); the tool is registered when any connection enables it. Off by default. |
Multiple connections
By default the bare CUBRID_* variables define a single connection named default.
You can serve additional CUBRID databases from the same process by listing extra
connection names in CUBRID_CONNECTIONS (comma-separated) and providingCUBRID_<NAME>_* variables for each. Every tool accepts an optional connection
argument selecting which connection to target; omitting it (or passing default)
uses the bare-variable connection, so existing single-database setups are unchanged.
# Default connection (unchanged)
export CUBRID_HOST=localhost
export CUBRID_USER=readonly_user
export CUBRID_PASSWORD=secret
export CUBRID_DATABASE=mydb
# Additional named connections
export CUBRID_CONNECTIONS=reporting,analytics
export CUBRID_REPORTING_HOST=reporting-db
export CUBRID_REPORTING_USER=readonly_user
export CUBRID_REPORTING_PASSWORD=secret
export CUBRID_REPORTING_DATABASE=reports
export CUBRID_REPORTING_MCP_MAX_ROWS=500 # optional per-connection tuning
export CUBRID_ANALYTICS_HOST=analytics-db
export CUBRID_ANALYTICS_USER=readonly_user
export CUBRID_ANALYTICS_PASSWORD=secret
export CUBRID_ANALYTICS_DATABASE=analytics
Notes:
- Connection names must match
[A-Za-z0-9_]+and are matched case-insensitively. defaultis reserved (it always comes from the bareCUBRID_*variables) and
cannot appear inCUBRID_CONNECTIONS.- For a named connection
<NAME>, connection fields live atCUBRID_<NAME>_HOST
etc. and the optional MCP tuning knobs atCUBRID_<NAME>_MCP_*(same suffixes as
the global ones). Named connections do not inherit values from the bare vars. - Selecting an unknown connection returns a clear error listing the available names.
- Each connection has its own read-only enforcement, so a named connection can set
CUBRID_<NAME>_MCP_READONLYindependently of the default.
Run
Run from PyPI
Use uvx to run directly from PyPI:
uvx cubrid-mcp-server
Or with pipx:
pipx run cubrid-mcp-server
Run from source
git clone https://github.com/cubrid-lab/cubrid-mcp-server.git
cd cubrid-mcp-server
python -m venv .venv && source .venv/bin/activate
pip install -e .
cubrid-mcp-server
MCP Client Integration
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"cubrid": {
"command": "uvx",
"args": ["cubrid-mcp-server"],
"env": {
"CUBRID_HOST": "localhost",
"CUBRID_USER": "readonly_user",
"CUBRID_PASSWORD": "secret",
"CUBRID_DATABASE": "mydb"
}
}
}
}
Claude Code
Add to .mcp.json in your project root:
{
"mcpServers": {
"cubrid": {
"command": "uvx",
"args": ["cubrid-mcp-server"],
"env": {
"CUBRID_HOST": "localhost",
"CUBRID_USER": "readonly_user",
"CUBRID_PASSWORD": "secret",
"CUBRID_DATABASE": "mydb"
}
}
}
}
Cursor
Add to .cursor/mcp.json:
{
"mcpServers": {
"cubrid": {
"command": "uvx",
"args": ["cubrid-mcp-server"],
"env": {
"CUBRID_HOST": "localhost",
"CUBRID_USER": "readonly_user",
"CUBRID_PASSWORD": "secret",
"CUBRID_DATABASE": "mydb"
}
}
}
}
Security
The server is read-only by default. A code-level SQL whitelist allows only SELECT, SHOW, DESC, DESCRIBE, EXPLAIN, and WITH statements. Multi-statement queries are rejected.
The SQL whitelist is defense-in-depth, not a security boundary. It is a non-validating parser-based guardrail against obvious mistakes. The real enforcement layer is the database itself: always run the server as a CUBRID user that has only
SELECTgrants on the tables the model may read. SeeSECURITY.md.
For production use, also configure a read-only database user. See SECURITY.md for the recommended setup.
Write mode (opt-in)
Write access is disabled by default. Setting CUBRID_MCP_WRITE=1 registers an additional execute_write tool that accepts a single INSERT, UPDATE, or DELETE statement and runs it in an explicit transaction (commit on success, rollback on any error). When write mode is off the tool is not registered at all, so no write path is exposed in MCP capability discovery. With multiple connections configured, the tool is registered when any connection enables writes (via CUBRID_MCP_WRITE or CUBRID_<NAME>_MCP_WRITE).
Constraints and rationale:
- Single-statement DML only. Standalone reads, DDL (
CREATE/ALTER/DROP/TRUNCATE), transaction-control, and multi-statement input are rejected. (A single DML statement may still legally contain subqueries, e.g.INSERT ... SELECT.) - DDL is intentionally unsupported. CUBRID auto-commits DDL, which defeats the rollback guarantee, so it is excluded from write mode.
- Write mode is per-connection.
execute_writeaccepts the same optionalconnectionargument as the read tools and runs against that connection; a connection whoseCUBRID_<NAME>_MCP_WRITEis off refuses the write even when another connection enables it. execute_queryremains read-only regardless of the write-mode flag.- Enforcement is defense-in-depth; still run the server as a CUBRID user granted only the privileges it needs. See
SECURITY.md.
Logging
The server speaks the MCP stdio transport, where stdout carries the JSON-RPC protocol stream. Anything written to stdout by the server or its dependencies will corrupt that stream and break the client connection. For this reason all logging is routed to stderr, and you should keep it that way: when adding custom logging or diagnostics, never print() to stdout — use the standard logging module (which is configured to emit on stderr) or write to stderr explicitly. The log level defaults to INFO.
Errors surfaced back to the LLM client are sanitized: only the exception category (e.g. query failed: OperationalError) is returned, while the full exception detail is logged to stderr for operators. This keeps schema details, hostnames, SQL fragments, and configuration values out of client-visible messages.
Audit logging (opt-in)
Set CUBRID_MCP_AUDIT_LOG=1 to record every executed statement (execute_query, explain_query, and execute_write) as a single structured JSON line on stderr. It is off by default and honoured per connection — a named connection sets CUBRID_<NAME>_MCP_AUDIT_LOG independently of the default. Each record is redaction-safe and contains only:
| Field | Description |
|---|---|
tool |
The MCP tool that ran the statement (execute_query / explain_query / execute_write). |
status |
ok or error. |
category |
The leading SQL keyword only (e.g. SELECT, WITH) — never the full statement. |
identifiers |
Table names extracted after FROM/JOIN via a strict identifier regex; anything that is not a bare identifier (values, literals, expressions) is dropped. |
sql_length |
Length of the submitted SQL, in characters. |
row_count, truncated |
Result size and whether output was truncated (success only). |
duration_ms |
Wall-clock duration of the call, in integer milliseconds. |
error_type |
On failure, the exception class name only (via the same sanitization as client-facing errors). |
The raw SQL text, bound parameters, and literal values are never logged, so secrets embedded in a query (e.g. WHERE token = '...') do not reach the audit stream. Records go to stderr only and never to stdout.
Development
git clone https://github.com/cubrid-lab/cubrid-mcp-server.git
cd cubrid-mcp-server
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
# Lint & type check
ruff check .
mypy cubrid_mcp_server
# Unit tests
pytest -m "not integration"
# Integration tests (requires running CUBRID)
export CUBRID_HOST=localhost CUBRID_USER=dba CUBRID_PASSWORD="" CUBRID_DATABASE=demodb
pytest -m integration
Related Projects
- pycubrid — Pure-Python DB-API 2.0 driver this server is built on
- sqlalchemy-cubrid — SQLAlchemy 2.0–2.2 dialect for CUBRID
- cubrid-cookbook-python — 68 runnable examples incl. one-command app templates that use this stack
Disclaimer
This project is part of CUBRID Lab, an independent open-source initiative for CUBRID developer tooling, and is not affiliated with, sponsored by, or endorsed by CUBRID Corporation or the official CUBRID project.
License
MIT (see LICENSE).
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