MCP Firebird
Implementation of Anthropic's MCP protocol for Firebird databases.
What is MCP Firebird and what is it for?
MCP Firebird is a server that implements Anthropic's Model Context Protocol (MCP) for Firebird SQL databases. It allows Large Language Models (LLMs) like Claude to access, analyze, and manipulate data in Firebird databases securely and in a controlled manner.
You'll find use cases and examples below.
Installation
# Global installation
npm install -g mcp-firebird
# Project installation
npm install mcp-firebird
Configuration
Environment Variables
You can configure the server using environment variables:
# Basic configuration
export FIREBIRD_HOST=localhost
export FIREBIRD_PORT=3050
export FIREBIRD_DATABASE=/path/to/database.fdb
export FIREBIRD_USER=SYSDBA
export FIREBIRD_PASSWORD=masterkey
export FIREBIRD_ROLE=undefined # Optional
# Directory configuration (alternative)
export FIREBIRD_DATABASE_DIR=/path/to/databases # Directory with databases
Using with npx
You can run the server directly with npx:
npx mcp-firebird --host localhost --port 3050 --database /path/to/database.fdb --user SYSDBA --password masterkey
Configuration with Claude Desktop
To use the Firebird MCP server with Claude Desktop:
Add the following configuration:
{
"mcpServers": {
"mcp-firebird": {
"command": "npx",
"args": [
"mcp-firebird",
"--host",
"localhost",
"--port",
"3050",
"--database",
"C:\\Databases\\example.fdb",
"--user",
"SYSDBA",
"--password",
"masterkey"
]
}
}
}
Resources and Features
The MCP Firebird server offers:
- Databases: List of all available databases
- Tables: List of all tables in the database
- Views: List of all views in the database
- Stored procedures: Access to procedures in the database
- Table schemas: Detailed structure of each table
- Data: Access to table data
- list-tables: Lists all tables in the database
{} // No parameters required
- describe-table: Describes the structure of a table
{
"tableName": "EMPLOYEES"
}
- execute-query: Executes an SQL query in the database
{
"sql": "SELECT * FROM EMPLOYEES WHERE DEPARTMENT_ID = 10",
"params": [] // Optional parameters for prepared queries
}
- get-field-descriptions: Gets field descriptions
{
"tableName": "EMPLOYEES"
}
The get-field-descriptions tool is especially useful for AI models, as it retrieves comments from Firebird's RDB$DESCRIPTION metadata, providing additional semantic context about the purpose of each field.
Available Prompts
- query-data: Query data using natural language
Find all employees in the sales department hired in 2023
- analyze-table: Analyze the structure of a table
Analyze the EMPLOYEES table and explain its structure
- optimize-query: Optimize an SQL query
Optimize: SELECT * FROM EMPLOYEES WHERE LAST_NAME = 'Smith'
- generate-sql: Generate SQL from a description
Generate a query to get the 10 best-selling products
Usage from Different Languages
TypeScript/JavaScript
// Example with TypeScript
import { McpClient, ChildProcessTransport } from '@modelcontextprotocol/sdk';
import { spawn } from 'child_process';
async function main() {
// Start the MCP server process
const serverProcess = spawn('npx', [
'mcp-firebird',
'--database', '/path/to/database.fdb',
'--user', 'SYSDBA',
'--password', 'masterkey'
]);
// Create a transport and an MCP client
const transport = new ChildProcessTransport(serverProcess);
const client = new McpClient(transport);
try {
// Get server information
const serverInfo = await client.getServerInfo();
console.log('MCP Server:', serverInfo);
// List available tables
const tablesResult = await client.executeTool('list-tables', {});
console.log('Available tables:', tablesResult);
// Execute an SQL query
const queryResult = await client.executeTool('execute-query', {
sql: 'SELECT FIRST 10 * FROM EMPLOYEES'
});
console.log('Query results:', queryResult);
// Use a prompt to generate SQL
const sqlGeneration = await client.executePrompt('generate-sql', {
description: 'Get all premium customers'
});
console.log('Generated SQL:', sqlGeneration);
} catch (error) {
console.error('Error:', error);
} finally {
// Close the server process
serverProcess.kill();
}
}
main().catch(console.error);
Python
# Example with Python
import json
import subprocess
from subprocess import PIPE
class McpFirebirdClient:
def __init__(self, database_path, user='SYSDBA', password='masterkey'):
# Start the MCP server process
self.process = subprocess.Popen(
['npx', 'mcp-firebird', '--database', database_path, '--user', user, '--password', password],
stdin=PIPE,
stdout=PIPE,
stderr=PIPE,
text=True,
bufsize=1
)
def send_request(self, method, params={}):
request = {
'id': 1,
'method': method,
'params': params
}
# Send the request to the server
self.process.stdin.write(json.dumps(request) + '\n')
self.process.stdin.flush()
# Read the response
response_line = self.process.stdout.readline()
while not response_line.strip() or response_line.startswith('['):
response_line = self.process.stdout.readline()
# Parse and return the JSON response
return json.loads(response_line)
def get_server_info(self):
return self.send_request('getServerInfo')
def list_tables(self):
return self.send_request('executeTool', {'name': 'list-tables', 'args': {}})
def execute_query(self, sql, params=[]):
return self.send_request('executeTool', {
'name': 'execute-query',
'args': {'sql': sql, 'params': params}
})
def generate_sql(self, description):
return self.send_request('executePrompt', {
'name': 'generate-sql',
'args': {'description': description}
})
def close(self):
self.process.terminate()
# Client usage
client = McpFirebirdClient('/path/to/database.fdb')
try:
# Get server information
server_info = client.get_server_info()
print(f"MCP Server: {server_info}")
# List tables
tables = client.list_tables()
print(f"Available tables: {tables}")
# Execute a query
results = client.execute_query("SELECT FIRST 10 * FROM EMPLOYEES")
print(f"Results: {results}")
# Generate SQL
sql = client.generate_sql("List the best-selling products")
print(f"Generated SQL: {sql}")
finally:
client.close()
Delphi and Lazurus
// Example with Delphi
program McpFirebirdClient;
{$APPTYPE CONSOLE}
uses
System.SysUtils, System.Classes, System.JSON, System.Net.HttpClient,
System.Diagnostics, System.IOUtils;
type
TMcpFirebirdClient = class
private
FProcess: TProcess; //For Delphi change to TProcessDelphi and add https://github.com/ferruhkoroglu/TProcessDelphi
FRequestId: Integer;
function SendRequest(const Method: string; const Params: TJSONObject = nil): TJSONObject;
function ReadResponse: string;
public
constructor Create(const DatabasePath, User, Password: string);
destructor Destroy; override;
function GetServerInfo: TJSONObject;
function ListTables: TJSONObject;
function ExecuteQuery(const SQL: string; Params: TArray<Variant> = nil): TJSONObject;
function GenerateSQL(const Description: string): TJSONObject;
end;
constructor TMcpFirebirdClient.Create(const DatabasePath, User, Password: string);
begin
inherited Create;
FRequestId := 1;
// Create and configure the process
FProcess := TProcess.Create(nil);
FProcess.Executable := 'npx';
FProcess.Parameters.Add('mcp-firebird');
FProcess.Parameters.Add('--database');
FProcess.Parameters.Add(DatabasePath);
FProcess.Parameters.Add('--user');
FProcess.Parameters.Add(User);
FProcess.Parameters.Add('--password');
FProcess.Parameters.Add(Password);
FProcess.Options := [poUsePipes, poStderrToOutPut];
FProcess.Execute;
// Wait for the server to start
Sleep(2000);
end;
destructor TMcpFirebirdClient.Destroy;
begin
FProcess.Free;
inherited;
end;
function TMcpFirebirdClient.SendRequest(const Method: string; const Params: TJSONObject = nil): TJSONObject;
var
Request: TJSONObject;
RequestStr, ResponseStr: string;
begin
// Create the JSON request
Request := TJSONObject.Create;
try
Request.AddPair('id', TJSONNumber.Create(FRequestId));
Inc(FRequestId);
Request.AddPair('method', Method);
if Assigned(Params) then
Request.AddPair('params', Params)
else
Request.AddPair('params', TJSONObject.Create);
RequestStr := Request.ToString + #10;
// Send the request to the process
FProcess.Input.Write(RequestStr[1], Length(RequestStr) * 2);
// Read the response
ResponseStr := ReadResponse;
Result := TJSONObject.ParseJSONValue(ResponseStr) as TJSONObject;
finally
Request.Free;
end;
end;
function TMcpFirebirdClient.ReadResponse: string;
var
Buffer: TBytes;
BytesRead: Integer;
ResponseStr: string;
begin
SetLength(Buffer, 4096);
ResponseStr := '';
repeat
BytesRead := FProcess.Output.Read(Buffer[0], Length(Buffer));
if BytesRead > 0 then
begin
SetLength(Buffer, BytesRead);
ResponseStr := ResponseStr + TEncoding.UTF8.GetString(Buffer);
end;
until BytesRead = 0;
Result := ResponseStr;
end;
function TMcpFirebirdClient.GetServerInfo: TJSONObject;
begin
Result := SendRequest('getServerInfo');
end;
function TMcpFirebirdClient.ListTables: TJSONObject;
var
Params: TJSONObject;
begin
Params := TJSONObject.Create;
try
Params.AddPair('name', 'list-tables');
Params.AddPair('args', TJSONObject.Create);
Result := SendRequest('executeTool', Params);
finally
Params.Free;
end;
end;
function TMcpFirebirdClient.ExecuteQuery(const SQL: string; Params: TArray<Variant> = nil): TJSONObject;
var
RequestParams, Args: TJSONObject;
ParamsArray: TJSONArray;
I: Integer;
begin
RequestParams := TJSONObject.Create;
Args := TJSONObject.Create;
ParamsArray := TJSONArray.Create;
try
// Configure the arguments
Args.AddPair('sql', SQL);
if Length(Params) > 0 then
begin
for I := 0 to Length(Params) - 1 do
begin
case VarType(Params[I]) of
varInteger: ParamsArray.Add(TJSONNumber.Create(Integer(Params[I])));
varDouble: ParamsArray.Add(TJSONNumber.Create(Double(Params[I])));
varBoolean: ParamsArray.Add(TJSONBool.Create(Boolean(Params[I])));
else ParamsArray.Add(String(Params[I]));
end;
end;
end;
Args.AddPair('params', ParamsArray);
RequestParams.AddPair('name', 'execute-query');
RequestParams.AddPair('args', Args);
Result := SendRequest('executeTool', RequestParams);
finally
RequestParams.Free;
end;
end;
function TMcpFirebirdClient.GenerateSQL(const Description: string): TJSONObject;
var
RequestParams, Args: TJSONObject;
begin
RequestParams := TJSONObject.Create;
Args := TJSONObject.Create;
try
Args.AddPair('description', Description);
RequestParams.AddPair('name', 'generate-sql');
RequestParams.AddPair('args', Args);
Result := SendRequest('executePrompt', RequestParams);
finally
RequestParams.Free;
end;
end;
var
Client: TMcpFirebirdClient;
ServerInfo, Tables, QueryResults, GeneratedSQL: TJSONObject;
begin
try
WriteLn('Starting MCP Firebird client...');
// Create the client
Client := TMcpFirebirdClient.Create('C:\Databases\example.fdb', 'SYSDBA', 'masterkey');
try
// Get server information
ServerInfo := Client.GetServerInfo;
WriteLn('Server information: ', ServerInfo.ToString);
// List tables
Tables := Client.ListTables;
WriteLn('Available tables: ', Tables.ToString);
// Execute a query
QueryResults := Client.ExecuteQuery('SELECT FIRST 10 * FROM EMPLOYEES');
WriteLn('Query results: ', QueryResults.ToString);
// Generate SQL
GeneratedSQL := Client.GenerateSQL('Get all premium customers');
WriteLn('Generated SQL: ', GeneratedSQL.ToString);
finally
Client.Free;
end;
except
on E: Exception do
WriteLn('Error: ', E.Message);
end;
WriteLn('Press ENTER to exit...');
ReadLn;
end.
Docker Configuration
You can run the MCP Firebird server in a Docker container:
Dockerfile
FROM node:18-alpine
# Install necessary dependencies for Firebird
RUN apk add --no-cache firebird-client
# Create application directory
WORKDIR /app
# Copy project files
COPY package*.json ./
RUN npm install
# Copy source code
COPY . .
# Compile the TypeScript project
RUN npm run build
# Expose port if HTTP is used (optional)
# EXPOSE 3000
# Set default environment variables
ENV FIREBIRD_HOST=firebird-db
ENV FIREBIRD_PORT=3050
ENV FIREBIRD_USER=SYSDBA
ENV FIREBIRD_PASSWORD=masterkey
ENV FIREBIRD_DATABASE=/firebird/data/database.fdb
# Start command
CMD ["node", "dist/index.js"]
Docker Compose
version: '3.8'
services:
# Firebird database server
firebird-db:
image: jacobalberty/firebird:3.0
environment:
ISC_PASSWORD: masterkey
FIREBIRD_DATABASE: database.fdb
FIREBIRD_USER: SYSDBA
volumes:
- firebird-data:/firebird/data
ports:
- "3050:3050"
networks:
- mcp-network
# MCP Firebird server
mcp-firebird:
build:
context: .
dockerfile: Dockerfile
environment:
FIREBIRD_HOST: firebird-db
FIREBIRD_PORT: 3050
FIREBIRD_USER: SYSDBA
FIREBIRD_PASSWORD: masterkey
FIREBIRD_DATABASE: /firebird/data/database.fdb
depends_on:
- firebird-db
networks:
- mcp-network
# For use with Claude Desktop, expose STDIO
stdin_open: true
tty: true
networks:
mcp-network:
driver: bridge
volumes:
firebird-data:
Running with Docker
# Build and run with Docker Compose
docker compose up -d
# Check logs
docker compose logs -f mcp-firebird
# Stop services
docker compose down
Use Cases
- Data Analysis with AI:
- Analyze historical sales trends
- Identify patterns in financial data
- Detect anomalies in transaction records
- SQL Query Generation:
- Create complex queries from natural language descriptions
- Optimize existing queries to improve performance
- Translate queries between different SQL dialects
- Automated Documentation:
- Generate documentation about database structure
- Explain relationships between tables and schemas
- Create detailed data dictionaries
- Development Assistance:
- Suggest indexes to improve performance
- Propose schema normalizations
- Help with data migration between systems
Example of Sales Analysis Usage
Interaction with Claude:
User: Connect to my Firebird database and analyze sales trends by region in the last quarter.
Claude: I'll connect to your Firebird database to analyze regional sales trends.
[Claude uses MCP Firebird to execute several SQL queries]
Based on data from the last quarter, I've identified the following trends:
1. The North region has experienced 12.5% growth compared to the previous quarter
2. The South region shows a 3.2% decrease in electronics products
3. The "Laptop Pro X" product is the best-selling across all regions
4. Sales in the East region show a cyclical pattern with peaks on weekends
Graphically, the distribution of sales by region is:
[Graph generated by Claude based on the data]
Would you like to delve deeper into any specific region or product category?
Example of Query Optimization
User: I have this query that's running slowly, can you optimize it?
SELECT c.CUSTOMER_NAME, SUM(o.ORDER_TOTAL)
FROM CUSTOMERS c
JOIN ORDERS o ON c.CUSTOMER_ID = o.CUSTOMER_ID
WHERE o.ORDER_DATE > '2024-01-01'
GROUP BY c.CUSTOMER_NAME
ORDER BY SUM(o.ORDER_TOTAL) DESC
Claude: I'll analyze this query to optimize it.
[Claude uses MCP Firebird to analyze the schema and query]
I've identified several optimization opportunities:
1. The current query doesn't efficiently use indexes
2. The calculation of SUM(o.ORDER_TOTAL) is performed twice
Here's the optimized version:
```sql
SELECT c.CUSTOMER_NAME, total_sales
FROM CUSTOMERS c
JOIN (
SELECT CUSTOMER_ID, SUM(ORDER_TOTAL) as total_sales
FROM ORDERS
WHERE ORDER_DATE > '2024-01-01'
GROUP BY CUSTOMER_ID
) o ON c.CUSTOMER_ID = o.CUSTOMER_ID
ORDER BY total_sales DESC
This version:
- Reduces the dataset before joining
- Calculates the sum only once
- Could benefit from an index on ORDERS(ORDER_DATE, CUSTOMER_ID, ORDER_TOTAL)
When running both queries on your database, the optimized version is approximately 45% faster.
## Security Configuration
Security is a priority in MCP Firebird. Below are advanced options to control access and permitted operations.
### Limiting Access to Tables and Views
You can restrict which tables and views are available to the MCP server using inclusion and exclusion filters:
```javascript
// In your custom configuration (config.js)
module.exports = {
// Basic configuration...
security: {
// Only allow access to these tables
allowedTables: [
'CUSTOMERS',
'PRODUCTS',
'ORDERS',
'ORDER_ITEMS'
],
// Explicitly exclude these tables (takes precedence over allowedTables)
forbiddenTables: [
'USERS',
'USER_CREDENTIALS',
'AUDIT_LOG'
],
// Table name pattern filter (regular expression)
tableNamePattern: '^(?!TMP_|TEMP_|BAK_).*$' // Exclude temporary/backup tables
}
};
To use this configuration:
npx mcp-firebird --config ./config.js
Limiting SQL Operations
You can restrict which SQL operations are allowed:
// In your custom configuration
module.exports = {
// Basic configuration...
security: {
// Allowed SQL operations
allowedOperations: ['SELECT', 'EXECUTE'], // Only queries and stored procedures
// Specifically block these operations
forbiddenOperations: ['DROP', 'TRUNCATE', 'ALTER', 'GRANT', 'REVOKE'],
// Maximum number of rows that can be returned in a query
maxRows: 1000,
// Maximum query execution time (in ms)
queryTimeout: 5000
}
};
Restricting Sensitive Data
You can configure rules to mask or filter sensitive data:
module.exports = {
// Basic configuration...
security: {
dataMasking: [
{
// Mask specific columns
columns: ['CREDIT_CARD_NUMBER', 'SSN', 'PASSWORD'],
pattern: /^.*/,
replacement: '************'
},
{
// Partially mask emails
columns: ['EMAIL'],
pattern: /^(.{3})(.*)(@.*)$/,
replacement: '$1***$3'
}
],
// Row filters to exclude sensitive data
rowFilters: {
'CUSTOMERS': 'GDPR_CONSENT = 1', // Only show customers with GDPR consent
'EMPLOYEES': 'IS_PUBLIC_PROFILE = 1' // Only public employee profiles
}
}
};
Audit Logging
Configure detailed logging of all operations performed through MCP:
module.exports = {
// Basic configuration...
security: {
audit: {
// Enable auditing
enabled: true,
// Audit log destination
destination: 'database', // options: 'file', 'database', 'both'
// If destination includes 'file'
auditFile: '/path/to/audit.log',
// If destination includes 'database'
auditTable: 'MCP_AUDIT_LOG',
// Detail level
detailLevel: 'full', // 'basic', 'medium', 'full'
// What to log
logQueries: true,
logResponses: true,
logParameters: true
}
}
};
Audit Logging Example
-- Table structure for auditing
CREATE TABLE MCP_AUDIT_LOG (
LOG_ID INT NOT NULL PRIMARY KEY,
TIMESTAMP TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
CLIENT_INFO VARCHAR(255),
OPERATION_TYPE VARCHAR(50),
TARGET_OBJECT VARCHAR(100),
QUERY_TEXT BLOB SUB_TYPE TEXT,
PARAMETERS BLOB SUB_TYPE TEXT,
AFFECTED_ROWS INT,
EXECUTION_TIME INT,
USER_IDENTIFIER VARCHAR(100),
SUCCESS BOOLEAN
);
-- Example log entry
INSERT INTO MCP_AUDIT_LOG (
LOG_ID, CLIENT_INFO, OPERATION_TYPE, TARGET_OBJECT,
QUERY_TEXT, PARAMETERS, AFFECTED_ROWS,
EXECUTION_TIME, USER_IDENTIFIER, SUCCESS
) VALUES (
NEXT VALUE FOR SEQ_AUDIT_LOG, 'Claude/agent', 'SELECT', 'CUSTOMERS',
'SELECT CUSTOMER_NAME, CITY FROM CUSTOMERS WHERE REGION = ?',
'["East"]', 24, 45, 'claude-session-123', TRUE
);
Data Volume Limitations
Configure limits to prevent queries that consume too many resources:
module.exports = {
// Basic configuration...
security: {
resourceLimits: {
// Row limit per query
maxRowsPerQuery: 5000,
// Result size limit (in bytes)
maxResponseSize: 1024 * 1024 * 5, // 5 MB
// CPU time limit per query (ms)
maxQueryCpuTime: 10000,
// Query limit per session
maxQueriesPerSession: 100,
// Rate limiting (queries per minute)
rateLimit: {
queriesPerMinute: 60,
burstLimit: 20
}
}
}
};
Integration with External Authorization Systems
MCP Firebird can integrate with external authorization systems for more precise access control:
module.exports = {
// Basic configuration...
security: {
authorization: {
// Use an external authorization service
type: 'oauth2',
// Configuration for OAuth2
oauth2: {
tokenVerifyUrl: 'https://auth.example.com/verify',
clientId: 'mcp-firebird-client',
clientSecret: process.env.OAUTH_CLIENT_SECRET,
scope: 'database:read'
},
// Role to permission mapping
rolePermissions: {
'analyst': {
tables: ['SALES', 'PRODUCTS', 'CUSTOMERS'],
operations: ['SELECT']
},
'manager': {
tables: ['SALES', 'PRODUCTS', 'CUSTOMERS', 'EMPLOYEES'],
operations: ['SELECT', 'INSERT', 'UPDATE']
},
'admin': {
allTablesAllowed: true,
operations: ['SELECT', 'INSERT', 'UPDATE', 'DELETE']
}
}
}
}
};
Practical Security Examples
Example 1: MCP Server for Sales Analysis
// config-sales-analysis.js
module.exports = {
database: process.env.FIREBIRD_DATABASE,
user: process.env.FIREBIRD_USER,
password: process.env.FIREBIRD_PASSWORD,
security: {
// Limited access to sales tables
allowedTables: [
'SALES', 'PRODUCTS', 'CUSTOMERS', 'REGIONS',
'SALES_TARGETS', 'PRODUCT_CATEGORIES'
],
// Only allow SELECT queries
allowedOperations: ['SELECT'],
// Mask sensitive customer data
dataMasking: [
{
columns: ['CUSTOMER_EMAIL', 'CUSTOMER_PHONE'],
pattern: /^.*/,
replacement: '[REDACTED]'
}
],
// Resource limits
resourceLimits: {
maxRowsPerQuery: 10000,
maxQueryCpuTime: 5000
}
}
};
Claude Desktop config:
{
"mcpServers": {
"mcp-firebird-sales": {
"command": "npx",
"args": [
"mcp-firebird",
"--config",
"C:\\config\\config-sales-analysis.js"
]
}
}
}
Example 2: MCP Server for Inventory Management
// config-inventory.js
module.exports = {
database: process.env.FIREBIRD_DATABASE,
user: process.env.FIREBIRD_USER,
password: process.env.FIREBIRD_PASSWORD,
security: {
// Access to inventory tables
allowedTables: [
'INVENTORY', 'PRODUCTS', 'WAREHOUSES',
'STOCK_MOVEMENTS', 'SUPPLIERS'
],
// Allow limited read and write operations
allowedOperations: ['SELECT', 'INSERT', 'UPDATE'],
// Prevent modification of historical records
rowFilters: {
'STOCK_MOVEMENTS': 'MOVEMENT_DATE > DATEADD(-30 DAY TO CURRENT_DATE)'
},
// Full auditing
audit: {
enabled: true,
destination: 'both',
auditFile: 'C:\\logs\\inventory-audit.log',
auditTable: 'MCP_INVENTORY_AUDIT',
detailLevel: 'full'
}
}
};
Example 3: Configuration for Development and Testing
// config-development.js
module.exports = {
database: process.env.FIREBIRD_DATABASE_DEV,
user: process.env.FIREBIRD_USER_DEV,
password: process.env.FIREBIRD_PASSWORD_DEV,
security: {
// In development, allow more operations
allowedOperations: ['SELECT', 'INSERT', 'UPDATE', 'DELETE', 'CREATE'],
// Exclude only critical tables
forbiddenTables: ['SYSTEM_CONFIG', 'APP_SECRETS'],
// Limit impact of heavy queries
resourceLimits: {
maxRowsPerQuery: 1000,
maxQueryCpuTime: 3000,
queriesPerMinute: 120
},
// Basic auditing
audit: {
enabled: true,
destination: 'file',
auditFile: './logs/dev-audit.log',
detailLevel: 'basic'
}
}
};
These examples illustrate how MCP Firebird can be configured for different use cases, each with its own security and data access considerations.
Integration with AI Agents
Claude in the Terminal
You can use the MCP Firebird server with Claude in the terminal:
# Start the MCP server in one terminal
npx mcp-firebird --database /path/to/database.fdb --user SYSDBA --password masterkey
# In another terminal, use anthropic CLI with MCP
anthropic messages create \
--model claude-3-opus-20240229 \
--max-tokens 4096 \
--mcp "npx mcp-firebird --database /path/to/database.fdb --user SYSDBA --password masterkey" \
--message "Analyze the structure of my Firebird database"
Other AI Agents
The MCP Firebird server is compatible with any agent that implements the MCP protocol, simply by providing the command to start the server:
npx mcp-firebird --database /path/to/database.fdb --user SYSDBA --password masterkey
Security
The server implements the following security measures:
- Input validation with Zod
- SQL query sanitization
- Secure credential handling
- SQL injection prevention
- Restriction of destructive operations
Debugging and Troubleshooting
To enable debug mode:
Common Issues
- Database connection error:
- Verify credentials and database path
- Make sure the Firebird server is running
- Check that the user has sufficient permissions
- Server doesn't appear in Claude Desktop:
- Restart Claude Desktop
- Verify the configuration in
claude_desktop_config.json
- Make sure the database path is absolute
- STDIO issues:
- Ensure standard output is not being redirected
- Don't use
console.log
for debugging (use console.error
instead)
License
MIT