Timeplus▌
by timeplus-io
Integrate Timeplus for real-time analytics and understand the execution order of SQL queries to optimize your data explo
Integrates with Timeplus to enable SQL query execution and database information retrieval for real-time analytics and data exploration.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Real-time analytics and data exploration
- / Streaming data engineers working with Kafka
- / Teams using Timeplus for time-series analysis
- / Data scientists querying streaming databases
capabilities
- / Execute SQL queries on Timeplus clusters
- / List databases and tables
- / Explore Kafka topics and messages
- / Create streaming ETL pipelines from Kafka
- / Connect to Apache Iceberg databases
- / Generate optimized SQL for Timeplus
what it does
Connects to Timeplus databases to run SQL queries and manage real-time streaming data. Includes tools for exploring Kafka topics and setting up streaming ETL pipelines.
about
Timeplus is a community-built MCP server published by timeplus-io that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate Timeplus for real-time analytics and understand the execution order of SQL queries to optimize your data explo It is categorized under databases.
how to install
You can install Timeplus in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
Apache-2.0
Timeplus is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Timeplus MCP Server
An MCP server for Timeplus.
<a href="https://glama.ai/mcp/servers/9aleefsq9s"><img width="380" height="200" src="https://glama.ai/mcp/servers/9aleefsq9s/badge" alt="mcp-timeplus MCP server" /></a>
Features
Prompts
generate_sqlto give LLM more knowledge about how to query Timeplus via SQL
Tools
-
run_sql- Execute SQL queries on your Timeplus cluster.
- Input:
sql(string): The SQL query to execute. - By default, all Timeplus queries are run with
readonly = 1to ensure they are safe. If you want to run DDL or DML queries, you can set the environment variableTIMEPLUS_READ_ONLYtofalse.
-
list_databases- List all databases on your Timeplus cluster.
-
list_tables- List all tables in a database.
- Input:
database(string): The name of the database.
-
list_kafka_topics- List all topics in a Kafka cluster
-
explore_kafka_topic- Show some messages in the Kafka topic
- Input:
topic(string): The name of the topic.message_count(int): The number of messages to show, default to 1.
-
create_kafka_stream- Setup a streaming ETL in Timeplus to save the Kafka messages locally
- Input:
topic(string): The name of the topic.
-
connect_to_apache_iceberg- Connect to a database based on Apache Iceberg. Currently this is only available via Timeplus Enterprise and it's planned to make it available for Timeplus Proton soon.
- Input:
iceberg_db(string): The name of the Iceberg database.aws_account_id(int): The AWS account ID (12 digits).s3_bucket(string): The S3 bucket name.aws_region(string): The AWS region, default to "us-west-2".is_s3_table_bucket(bool): Whether the S3 bucket is a S3 table bucket, default to False.
Configuration
First, ensure you have the uv executable installed. If not, you can install it by following the instructions here.
-
Open the Claude Desktop configuration file located at:
- On macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - On Windows:
%APPDATA%/Claude/claude_desktop_config.json
- On macOS:
-
Add the following:
{
"mcpServers": {
"mcp-timeplus": {
"command": "uvx",
"args": ["mcp-timeplus"],
"env": {
"TIMEPLUS_HOST": "<timeplus-host>",
"TIMEPLUS_PORT": "<timeplus-port>",
"TIMEPLUS_USER": "<timeplus-user>",
"TIMEPLUS_PASSWORD": "<timeplus-password>",
"TIMEPLUS_SECURE": "false",
"TIMEPLUS_VERIFY": "true",
"TIMEPLUS_CONNECT_TIMEOUT": "30",
"TIMEPLUS_SEND_RECEIVE_TIMEOUT": "30",
"TIMEPLUS_READ_ONLY": "false",
"TIMEPLUS_KAFKA_CONFIG": "{"bootstrap.servers":"a.aivencloud.com:28864", "sasl.mechanism":"SCRAM-SHA-256","sasl.username":"avnadmin", "sasl.password":"thePassword","security.protocol":"SASL_SSL","enable.ssl.certificate.verification":"false"}"
}
}
}
}
Update the environment variables to point to your own Timeplus service.
- Restart Claude Desktop to apply the changes.
You can also try this MCP server with other MCP clients, such as 5ire.
Development
-
In
test-servicesdirectory rundocker compose up -dto start a Timeplus Proton server. You can also download it viacurl https://install.timeplus.com/oss | sh, then start with./proton server. -
Add the following variables to a
.envfile in the root of the repository.
TIMEPLUS_HOST=localhost
TIMEPLUS_PORT=8123
TIMEPLUS_USER=default
TIMEPLUS_PASSWORD=
TIMEPLUS_SECURE=false
TIMEPLUS_VERIFY=true
TIMEPLUS_CONNECT_TIMEOUT=30
TIMEPLUS_SEND_RECEIVE_TIMEOUT=30
TIMEPLUS_READ_ONLY=false
TIMEPLUS_KAFKA_CONFIG={"bootstrap.servers":"a.aivencloud.com:28864", "sasl.mechanism":"SCRAM-SHA-256","sasl.username":"avnadmin", "sasl.password":"thePassword","security.protocol":"SASL_SSL","enable.ssl.certificate.verification":"false"}
-
Run
uv syncto install the dependencies. Then dosource .venv/bin/activate. -
For easy testing, you can run
mcp dev mcp_timeplus/mcp_server.pyto start the MCP server. Click the "Connect" button to connect the UI with the MCP server, then switch to the "Tools" tab to run the available tools. -
To build the Docker image, run
docker build -t mcp_timeplus ..
Environment Variables
The following environment variables are used to configure the Timeplus connection:
Required Variables
TIMEPLUS_HOST: The hostname of your Timeplus serverTIMEPLUS_USER: The username for authenticationTIMEPLUS_PASSWORD: The password for authentication
Optional Variables
TIMEPLUS_PORT: The port number of your Timeplus server- Default:
8443if HTTPS is enabled,8123if disabled - Usually doesn't need to be set unless using a non-standard port
- Default:
TIMEPLUS_SECURE: Enable/disable HTTPS connection- Default:
"false" - Set to
"true"for secure connections
- Default:
TIMEPLUS_VERIFY: Enable/disable SSL certificate verification- Default:
"true" - Set to
"false"to disable certificate verification (not recommended for production)
- Default:
TIMEPLUS_CONNECT_TIMEOUT: Connection timeout in seconds- Default:
"30" - Increase this value if you experience connection timeouts
- Default:
TIMEPLUS_SEND_RECEIVE_TIMEOUT: Send/receive timeout in seconds- Default:
"300" - Increase this value for long-running queries
- Default:
TIMEPLUS_DATABASE: Default database to use- Default: None (uses server default)
- Set this to automatically connect to a specific database
TIMEPLUS_READ_ONLY: Enable/disable read-only mode- Default:
"true" - Set to
"false"to enable DDL/DML
- Default:
TIMEPLUS_KAFKA_CONFIG: A JSON string for the Kafka configuration. Please refer to librdkafka configuration or take the above example as a reference.
FAQ
- What is the Timeplus MCP server?
- Timeplus is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Timeplus?
- This profile displays 71 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Direct Database Queries from AI
Enable Claude to query your database directly using natural language
Example
Ask 'Show me top 10 customers by revenue this month' and get SQL results instantly
Eliminate manual SQL writing for ad-hoc queries, get insights 10x faster
Data Analysis & Reporting
Generate complex reports and analytics without leaving conversation
Example
Analyze sales trends, cohort retention, user behavior patterns conversationally
Democratize data access—non-technical team members can query databases
Schema Exploration
Understand database structure, relationships, and data models
Example
'Explain the user_orders table schema and its relationships'
Onboard engineers faster, explore unfamiliar databases efficiently
Data Validation & Quality Checks
Run data quality queries to catch anomalies and inconsistencies
Example
Find duplicate records, missing values, orphaned foreign keys automatically
Maintain data integrity with less manual SQL work
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor with MCP support
- ›Database credentials (read-only recommended for safety)
- ›Network access from Claude client to database
- ›Understanding of database security and access control
Time Estimate
15-30 minutes including configuration and testing
Installation Steps
- 1.Install MCP server: npm install -g @modelcontextprotocol/server-[name]
- 2.Configure database connection in Claude Desktop config (~/.claude/mcp.json)
- 3.Provide connection string: host, port, database, username, password
- 4.Restart Claude Desktop to load MCP server
- 5.Test connection: 'List all tables in database'
- 6.Run simple query: 'Show me 5 rows from users table'
- 7.Verify results and permissions are correct
- 8.Document query patterns for team use
Troubleshooting
- ⚠Connection refused: Check database is running and network accessible
- ⚠Authentication failed: Verify credentials, check user permissions
- ⚠Claude can't see tables: Grant appropriate read permissions to database user
- ⚠Slow queries: Add indexes, limit result set size, use read replicas
- ⚠MCP server not loading: Check config syntax, restart Claude Desktop
Best Practices▌
✓ Do
- +Use read-only database credentials to prevent accidental writes
- +Connect to read replica, not production primary database
- +Set query timeout limits to prevent long-running queries
- +Document database schema and common queries for AI context
- +Monitor query performance and optimize slow queries
- +Use connection pooling for better performance
- +Test with non-production data first
✗ Don't
- −Don't use production write credentials—risk of data corruption
- −Don't query production database during peak traffic hours
- −Don't expose sensitive PII without proper access controls
- −Don't skip query result validation—AI can misinterpret schema
- −Don't allow unlimited result set sizes—set LIMIT clauses
- −Don't share database credentials in plain text config files
💡 Pro Tips
- ★Create database views for common queries to simplify AI access
- ★Add schema comments/descriptions so AI understands column meanings
- ★Use semantic table/column names ('customer_lifetime_value' not 'clv')
- ★Set up query logging to audit what Claude is querying
- ★Create saved query templates for recurring analysis
- ★Combine with data visualization tools for better insights
Technical Details▌
Architecture
MCP server acts as bridge between Claude and database, translating natural language to SQL queries and returning results in structured format.
Protocols
- Model Context Protocol (MCP)
- Database-specific protocols (PostgreSQL, MySQL, MongoDB)
Compatibility
- PostgreSQL
- MySQL
- SQLite
- MongoDB
- Redis
When to Use This▌
✓ Use When
Use for ad-hoc data queries, exploratory analysis, report generation, schema exploration, and democratizing data access. Best for read-heavy analytics workloads.
✗ Avoid When
Avoid for production write operations, mission-critical transactions, real-time OLTP workloads, or when database contains sensitive PII without proper access controls. Use read replicas, not primary.
Integration▌
- →Read replica connection for analytics queries
- →Database view layer to abstract complex joins
- →Query result caching for repeated questions
- →Audit logging of all AI-generated queries
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
List & Promote Your MCP Server
Share your MCP server with the developer community
Ratings
4.6★★★★★71 reviews- ★★★★★Charlotte Park· Dec 24, 2024
We wired Timeplus into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Shikha Mishra· Dec 20, 2024
Useful MCP listing: Timeplus is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Ganesh Mohane· Dec 16, 2024
Timeplus has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Zara Taylor· Dec 12, 2024
According to our notes, Timeplus benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Tariq Jain· Dec 12, 2024
Timeplus reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Sophia Torres· Dec 12, 2024
Strong directory entry: Timeplus surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Ira Desai· Dec 8, 2024
We wired Timeplus into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Camila Yang· Nov 27, 2024
We evaluated Timeplus against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Henry Jackson· Nov 19, 2024
Timeplus is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Zara Jackson· Nov 15, 2024
We evaluated Timeplus against two servers with overlapping tools; this profile had the clearer scope statement.
showing 1-10 of 71