Baidu Vector Database MCP Server
OfficialServer 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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_databasesB | |
| create_databaseC | |
| use_databaseB | |
| list_tablesB | |
| describe_tableB | |
| stats_tableC | |
| create_vector_indexA | |
| describe_indexC | |
| rebuild_vector_indexC | |
| delete_table_rowsC | |
| drop_vector_indexC | |
| select_table_rowsC | |
| vector_searchB | |
| fulltext_searchB | |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 14 tools
Most tools have distinct purposes targeting specific database operations like creation, description, listing, and search. However, some overlap exists between 'select_table_rows' and 'vector_search'/'fulltext_search' as they all retrieve data, though their search methods differ (filter expression vs. vector/full-text). The descriptions help clarify these distinctions.
All tool names follow a consistent verb_noun pattern with snake_case, such as 'create_database', 'list_tables', and 'describe_index'. There are no deviations in naming conventions, making the set predictable and easy to parse.
With 14 tools, the count is well-scoped for a vector database server, covering essential operations like database/table management, indexing, and search. Each tool serves a clear purpose without redundancy, fitting within the typical 3-15 range for such domains.
The toolset provides comprehensive coverage for core vector database workflows, including CRUD-like operations (create, list, describe, delete) and specialized searches. Minor gaps include missing tools for updating table schemas or rows directly, but agents can work around this using existing tools like 'select_table_rows' and 'delete_table_rows' in combination.