mcp-timeplus
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_databasesA | List available Timeplus databases |
| list_tablesC | List available tables/streams in the given database |
| run_sqlC | Run a query in a Timeplus database |
| list_kafka_topicsD | – |
| explore_kafka_topicD | – |
| create_kafka_streamD | – |
| connect_to_apache_icebergC | Create a Timeplus database in iceberg type to connect to Iceberg |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| generate_sql |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
Most tools target distinct actions: listing databases, listing tables, running SQL, and connecting Iceberg are clearly separate. However, list_kafka_topics and explore_kafka_topic have overlapping territory around Kafka topics, and create_kafka_stream is adjacent to them; the empty descriptions worsen the ambiguity.
All tool names follow a consistent verb_noun pattern in lowercase snake_case, such as list_databases, list_tables, and create_kafka_stream. The only slight deviation is connect_to_apache_iceberg, but it still follows the same verb-first convention.
Seven tools is a well-scoped set for a Timeplus MCP server, covering database exploration, SQL execution, Kafka integration, and Iceberg connectivity without bloating the surface.
The toolset covers core querying, table/database listing, and Kafka stream ingestion plus Iceberg connection. Minor gaps exist around resource management (e.g., creating/dropping regular databases or streams), but the main read and integration workflows are supported.