mcp-data-service
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-data-serviceWhat's the video with the highest completion rate?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Data Service · MCP 数据服务
Expose data query + auto-insights (anomaly detection) as an MCP Server — plug into Claude Desktop, Cursor, or any MCP client in 30 seconds. 把「数据查询 + 自动洞察」包装成 MCP 标准工具,Claude Desktop / Cursor 即插即用——给任意 AI Agent 装上数据能力,30 秒接入。
English · 中文
English
What is this?
An MCP (Model Context Protocol) server that turns a data table into callable tools for any AI agent. No LLM API needed — everything is computed locally with pandas, so it is free and fast.
Tools
Tool | What it does |
| Query by metric: TOP N / BOTTOM N / AVG / SUM / by date / with filter |
| Auto insights: overview + anomaly detection (1.5σ) + recommendations |
| List all column names and types |
Quick Start
pip install -r requirements.txt
# Self-test (direct calls + MCP handshake)
python tests/test_server.py
# Run the server (stdio transport; clients below will launch it automatically)
python server.pyConnect from Claude Desktop / Cursor
Add to your MCP config (e.g. claude_desktop_config.json):
{
"mcpServers": {
"data-service": {
"command": "python",
"args": ["/absolute/path/to/mcp-data-service/server.py"]
}
}
}Restart the client, then ask your agent: "What's the video with the highest completion rate?" or "Run auto insights on the data."
Project Layout
server.py FastMCP server (@mcp.tool registers 3 tools)
data/video_stats.csv Sample data
tests/test_server.py Direct-call + MCP-stdio handshake tests
requirements.txt fastmcp + pandasTests
python tests/test_server.py
# [PASS] query_video_stats direct calls
# [PASS] data_insights auto insights
# [PASS] MCP stdio handshake: list_tools + call_toolRoadmap
Publish to PyPI (
pipx install mcp-data-service)SQLite / PostgreSQL backend
Multiple data sources per server
中文
这是什么?
一个 MCP(Model Context Protocol) Server:把一张数据表变成任何 AI Agent 可调用的工具。完全不依赖 LLM API——全部用 pandas 本地计算,免费且快速。
工具清单
工具 | 作用 |
| 按指标查询:TOP N / BOTTOM N / 平均值 / 总和 / 按日期 / 带条件过滤 |
| 自动洞察:数据总览 + 异常下探(1.5σ)+ 运营建议 |
| 列出全部列名与类型 |
快速开始
pip install -r requirements.txt
# 自测(直接调用 + MCP 握手)
python tests/test_server.py
# 启动(stdio 传输,客户端按下面配置自动拉起)
python server.py接入 Claude Desktop / Cursor
在客户端 MCP 配置(如 claude_desktop_config.json)里加:
{
"mcpServers": {
"data-service": {
"command": "python",
"args": ["/绝对路径/mcp-data-service/server.py"]
}
}
}保存并重启客户端,即可让 Agent 直接调用「完播率最高的视频」「自动洞察数据异常」等能力。
文件结构
server.py FastMCP Server(@mcp.tool 注册 3 个工具)
data/video_stats.csv 示例数据
tests/test_server.py 直调 + MCP stdio 握手双测试
requirements.txt fastmcp + pandas测试
python tests/test_server.py
# [PASS] query_video_stats 直接调用
# [PASS] data_insights 自动洞察
# [PASS] MCP stdio 握手:list_tools + call_tool开发计划
发布 PyPI(
pipx install mcp-data-service)SQLite / PostgreSQL 后端
单个 Server 支持多个数据源
License · 许可证
MIT © lengzhanbao
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Real SEC, 13F, insider, congress & macro data your AI agent can cite. Hosted MCP, 24 tools.
Gateway between LLM agents and world data through eight tools and a bundled endpoint catalog.
Hosted MCP endpoint with realistic fake data for prototyping agents. 12 tools, no setup.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/lengzhanbao/mcp-data-service'
If you have feedback or need assistance with the MCP directory API, please join our Discord server