百度向量数据库 MCP Server

Model Context Protocol Server for Mochow

Local serverstdioPython

What is the 百度向量数据库 MCP server?

百度向量数据库 MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Model Context Protocol Server for Mochow.

What you get

在使用百度云向量数据库MCP Server之前,请确保你具备以下条件: 1. Python 3.10 或更高版本 2. 已安装uv用于运行MCP Server

Setting it up

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.

What the assistant can call

Once 百度向量数据库 is connected, these are the calls the assistant has available:

  • list_databases — 列出数据库中所有的Database
  • create_database — 创建一个新的Database
  • database_name — 待创建的Database名称
  • use_database — 切换到一个已存在的Database
  • list_tables — 列出数据库中所有的Table
  • describe_table — 获取指定Table的详细信息
  • table_name — Table名称
  • stats_table — 获取指定Table的统计信息
  • delete_table_rows — 使用过滤表达式删除数据
  • filter_expr — 过滤表达式
  • select_table_rows — 使用过滤表达式查询数据
  • limit — 查询结果的最大条数

Configuration and credentials

You will need one environment variable: MOCHOW_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

Before you rely on it

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 14 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch 百度向量数据库.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the 百度向量数据库 mcp server does with a few real requests.

Choosing this one

This sits in the database access group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. 百度向量数据库's toolset — list_databases, create_database, database_name and 11 more — is a fair guide to whether it matches your workflow. It is maintained by baidu; worth a glance at recent repository activity before you build anything load-bearing on it.

This entry was verified against 百度向量数据库's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.

Available tools

ToolWhat it does
list_databases列出数据库中所有的Database
create_database创建一个新的Database
database_name待创建的Database名称
use_database切换到一个已存在的Database
list_tables列出数据库中所有的Table
describe_table获取指定Table的详细信息
table_nameTable名称
stats_table获取指定Table的统计信息
delete_table_rows使用过滤表达式删除数据
filter_expr过滤表达式
select_table_rows使用过滤表达式查询数据
limit查询结果的最大条数
output_fields查询结果中要返回的字段名
create_vector_index在指定向量字段上创建向量索引

Configuration

VariableDescriptionRequired
MOCHOW_API_KEYCredential the server authenticates with.Yes

Example prompts to try

  • Use 百度向量数据库 to list databases.
  • Use 百度向量数据库 to create database.
  • Use 百度向量数据库 to database name.

Frequently asked questions

Python 3.10 or higher must be installed, along with the `uv` package runner.