"Connecting Feishu (Lark)" matching MCP servers:

Enables Claude to read Indonesia Stock Exchange (IDX/BEI) stock prices, compare stock performance, and calculate personal portfolio values directly in conversation. It is read-only and provides market status, historical returns including dividends, and portfolio warnings without connecting to brokerage accounts.

AI-powered MCP server for connecting and managing Jupyter Notebooks. Enables interactive code execution, multi-notebook management, and multimodal output for data analysis, visualization, and machine learning.

Enables natural language queries about grades, GPA, attendance, and schedules by connecting Claude to StudentVue school dashboards. Includes analytical tools for grade simulation, what-if scenarios, and academic performance tracking based on live school data.

Enables Claude to analyze personal finances by reading bank CSVs or connecting to Plaid for live transactions, categorizing spending, flagging overspending against benchmarks, and generating actionable reports and savings tips.

This MCP server enables AI-assisted professional profile generation by connecting to verified employee work data (skills, career history, certifications, projects) from employer HCM systems.

MCP server for connecting to Microsoft Fabric and Power BI semantic models, enabling workspace browsing, dataset management, TMSL retrieval, DAX queries, model creation/editing, and includes a Best Practice Analyzer with 71 rules.

An MCP server that enables AI agents to manage multi-marketplace e-commerce operations by connecting to the SellerChamp API. It supports inventory reporting, cross-listing analysis, order management, and bulk updates across platforms like Amazon, eBay, and Shopify.

Enables AI agents to fetch Xiaohongshu advertising data from Chengfeng, Juguang, and Dandelion platforms via MCP, and supports syncing daily ad reports to Feishu.

An MCP server that provides a unified interface for connecting LLM agents to many database types, including PostgreSQL, MySQL, SQLite, BigQuery, Oracle, MS SQL, and Redshift. It exposes schema retrieval and query execution endpoints, normalizing schemas and optimizing LLM-generated queries for compatibility.

Enables agents to query and manage inventory data from Feishu source tables, providing tools for stock checks, distribution analysis, alternatives, and weekly ledger updates.

Enables self-hosted personal finance management for MCP clients by connecting read-only bank accounts via SimpleFIN, syncing transactions into a local SQLite database, and exposing tools to query balances, spending, budgets, cash flow, and net worth.

Enables deterministic reconstruction of complex tables from OCR bounding boxes, including multi-column layouts, merged headers, grid hierarchies, formula auditing, and PII redaction through MCP.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

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.

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.

Enables autonomous agents to compute and atomically apply minimal JSON Patch (RFC 6902) operational diffs for structured data state synchronization. Runs as a zero-dependency Python MCP server supporting deterministic patching, caching, and rate-limiting workflows.

Enables document layout parsing, complex table reconstruction, formula auditing, and PII/credential redaction with Luhn verification, reversible salt hashing, and audit logs through MCP-compatible clients.

Enables multi-provider waterfall data enrichment for B2B prospects, firmographics, and verified decision-maker corporate emails via MCP.

Enables deterministic extraction and validation of structured JSON data from inputs using a defined schema. It plugs into MCP-compatible clients like Claude Desktop, Cursor, and Windsurf to return standardized, schema-validated results.