AI Agent for GreptimeDB MCP Server
Integrate GreptimeDB’s Model Context Protocol (MCP) server to enable AI assistants with secure, structured, and responsible access to your time-series database. Effortlessly list tables, read data, and execute SQL queries via a controlled interface, all while maintaining data integrity and simplifying database management.
Secure & Structured Database Access
Empower your AI agents to interact with GreptimeDB safely. The MCP server provides fine-grained resource listing, data reading, and SQL execution through a secure, configurable protocol—ensuring every access is controlled and auditable.
- Secure Protocol.
- AI assistants access only what you allow, ensuring database security and responsible usage.
- Table Listing.
- List and discover available tables in GreptimeDB via the MCP server.
- Data Exploration.
- Read table data with strict access controls, making analytics safe and efficient.
- Controlled SQL Execution.
- Run SQL queries through a managed interface, preventing unauthorized operations.
Flexible Integration & Configuration
Quickly connect GreptimeDB MCP server with your favorite AI tools, including Claude Desktop. Configure via environment variables or command-line for seamless deployment in any workflow.
- Easy Setup.
- Install via pip, configure via environment variables or CLI, and connect instantly.
- AI Tool Integration.
- Works with Claude Desktop and Model Context Protocol Inspector for streamlined AI workflows.
- Customizable Environment.
- Set host, port, credentials, and timezone to fit your infrastructure.
Developer-Friendly & Open Source
Built for developers, GreptimeDB MCP server is open source, MIT-licensed, and supports robust contribution and debugging workflows. Leverage the power of Python and GreptimeDB for scalable, AI-driven data solutions.
- Open Source.
- MIT-licensed and fully transparent, encouraging community collaboration.
- Debugging Tools.
- Use MCP Inspector and Python test suites for robust development and QA.
- Inspired by Community.
- Built on the shoulders of leading MCP server implementations, with gratitude to contributors.
MCP INTEGRATION
Available GreptimeDB MCP Integration Tools
The following tools are available as part of the GreptimeDB MCP integration:
- list_resources
List all available tables in the connected GreptimeDB database.
- read_resource
Read and retrieve data from a specified table, enabling data exploration.
- list_tools
List all available tools provided by the server for integration and automation.
- call_tool
Execute an SQL statement on the GreptimeDB database through a controlled interface.
- list_prompts
List all available prompt templates that can be used for various tasks.
- get_prompt
Retrieve a specific prompt template by its name for use in workflows.
Explore Secure AI-Assisted Database Access
See how greptimedb-mcp-server enables AI assistants to safely query, analyze, and interact with your GreptimeDB databases. Experience responsible and structured data exploration today.
What is GreptimeDB
GreptimeDB is an open-source, cloud-native, real-time observability database designed for the unified collection, storage, and analysis of metrics, logs, and traces. Built for high performance and scalability, GreptimeDB empowers organizations to monitor their infrastructure and applications efficiently at any scale. Its architecture allows for flexible deployment as a standalone instance or as a cluster, making it suitable for cloud, on-premises, and hybrid environments. GreptimeDB provides a cost-effective solution for observability by integrating with modern monitoring stacks and supporting SQL-like queries for quick insights. The platform is trusted by enterprises for handling large-scale telemetry and observability workloads with high reliability and low latency, making it an ideal choice for DevOps, SRE, and data engineering teams.
Capabilities
What we can do with GreptimeDB
With GreptimeDB, users can efficiently manage and analyze vast amounts of observability data, enabling real-time monitoring and actionable insights. The platform's capabilities support a wide range of operational and analytical use cases, from infrastructure monitoring to advanced telemetry analytics.
- Unified Observability
- Collect and analyze metrics, logs, and traces from diverse sources in a single platform.
- Real-Time Analytics
- Execute high-performance queries for instant insights into system health and performance.
- Scalable Deployments
- Deploy as a standalone instance or scale out as a distributed cluster to handle growing data needs.
- SQL-Like Query Language
- Use familiar SQL syntax to explore, aggregate, and visualize observability data.
- Seamless Integrations
- Easily connect with popular monitoring and alerting tools for end-to-end observability workflows.
How AI Agents Benefit from GreptimeDB
AI agents can leverage GreptimeDB to access real-time, high-fidelity observability data, enabling automated monitoring, anomaly detection, and dynamic resource optimization. By interfacing with GreptimeDB's APIs and query capabilities, AI agents can rapidly detect issues, trigger alerts, and recommend or execute corrective actions, enhancing system reliability and operational efficiency without manual intervention.