"Library Documentation" matching MCP servers:

Provides AI assistants with access to Vega-Lite documentation, visualization examples, and specification validation tools. Enables searching docs, retrieving examples by category, validating JSON specs, and accessing schema information for creating data visualizations.

A financial data server that provides real-time and historical data for A-shares, Hong Kong, and US markets using the AkShare library. It enables users to query market quotes, fundamental information, and technical indicators through the Model Context Protocol.

Enables agents to synchronize, merge, and reconcile distributed state across nodes using conflict-free last-write-wins element sets with Lamport/vector-clock causality, token-bucket gossip dissemination, and quorum-based commit coordination. It runs entirely on the Python standard library and exposes these primitives to Claude Desktop, Cursor, and Windsurf over the MCP JSON-RPC stdio protocol.

An MCP server and Go library that connects AI assistants to DataHub metadata catalogs, enabling dataset search, schema exploration, lineage tracing, and glossary access.

Enables generation of various chart types (bar, line, pie, scatter, radar, heatmap, and more) using ECharts library, returning preview URLs to visualize data through natural language requests.

Enables AI agents and MCP clients to heuristically parse multi-column document dumps, aligned spacing, and CSV/TSV input, converting them into clean GitHub Flavored Markdown tables and typed JSON. Runs fully offline on the Python standard library with zero external dependencies, returning deterministic results without LLM round-trips.

A Model Context Protocol server that enables Claude Desktop to access and analyze Chinese and global financial market data through the AKShare library.

Provides stock market data and trading capabilities using the yfinance library

Enables comprehensive SQLite database management through natural language including database creation, table operations, data CRUD operations, backup/restore, and CSV import/export functionality. Built on FastMCP framework with PySqlit library for reliable database interactions.

Provides access to historical financial data for US, Hong Kong, and A-share markets using the AkShare library. It returns formatted stock market data, including prices and trading volumes, in easy-to-read Markdown tables.

Generates complete PyAirbyte data pipeline code and setup instructions for moving data between 600+ Airbyte source and destination connectors or to Pandas DataFrames, using AI-powered context-aware guidance based on connector documentation.

MCP server for Formula 1 data via the FastF1 library. Ask Claude (or any MCP-compatible client) about race results, lap times, telemetry, standings, pit stops, and qualifying — with historical data back to 1950 via the Ergast API.

Enables AI clients to investigate data engineering workflows by exposing tools for job status, logs, schema lookup, read-only SQL, and searching documentation/incidents, along with resources and prompts for ETL failure analysis.