"A programming resource or code repository index" matching MCP servers:

Remote MCP server for querying financial index data, running backtests, and building/deploying systematic investment strategies from any MCP-capable client.

基于Model Context Protocol (MCP) 的A股实时行情查询服务器，支持查询A股实时价格、历史K线数据、财务信息及市场概况。

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Minimalistic MCP server that lets AI assistants inspect, quality-check, and clean CSV datasets through tools, resources, and prompts, without needing local file access.

A stdio MCP server exposing a validate_emails tool that lets agents screen email lists without sending mail or probing SMTP, checking syntax, DNS/MX records, disposable domains, role accounts, free providers, typo suggestions, and SPF/DMARC. Each address comes back with a valid/risky/invalid/unknown verdict plus machine-readable reason codes so agents can clean leads and signups before outreach or import.

Enables an AI assistant to answer customer-success questions by synthesizing simulated billing, support ticket, and product usage data into composite churn-risk scores, bands, and plain-language explanations for fictional accounts. It exposes raw-data tools, a synthesis tool, and a methodology resource so users can list at-risk accounts or get a per-account health summary.

A privacy-first MCP server that searches, normalizes, and deduplicates job listings across multiple providers, enabling trustworthy discovery without scoring or applying.

Vizro is a low-code toolkit for building high-quality data visualization apps.

This server acts as a MCP bridge to interact with the Cribl REST API. It allows AI models or other MCP clients to query and manage Cribl configurations.

A Model Context Protocol server that lets you fetch Microsoft Clarity analytics data through Claude for Desktop or other MCP-compatible clients, with support for filtering by dimensions and retrieving various metrics.

Enables converting data structure definitions between numerous schema formats and generating code for multiple programming languages, using Apache Avro Schema as the integration model.

Enables users to review a supplied batch of supplier invoices or vendor bills for repeated references, normalized reference variations, and identical amount-and-date candidates, returning grouped evidence and exact review reasons from local history. Supports saved reports, CSV export, and use with MCP clients such as Claude Desktop, Claude Code, and Cursor.

A server that interfaces with the Mixpanel API, allowing users to query events data, retention, and funnels through natural language from any MCP client like Cursor or Claude Desktop.

A Python MCP server for hypothesis-driven data analysis, managing analysis designs, data catalogs, and review workflows through Claude Code or any MCP-compatible client.

Local-first Taiwan market evidence workbench for AI agents with persistent Watchlists, governed MCP, auditable evidence, and explicit execute-once retrieval. GitHub Repository URL

A Model Context Protocol (MCP) server that provides tools for reading Excel (xlsx) files, enabling extraction of data from entire workbooks or specific sheets with results returned in structured JSON format.

Enables AI assistants to manage a GBIF IPT from resource creation to publication, including metadata editing, data validation, Darwin Core mapping, and publishing, through plain language requests.

A comprehensive MCP server for Dataiku DSS integration, providing Claude Code with direct access to manage recipes, datasets, and scenarios.

A Python MCP server that lets you manage Microsoft Fabric through natural language in Claude Code or Claude Desktop, with 77+ tools covering workspaces, lakehouses, warehouses, SQL, DAX, semantic models, notebooks, pipelines, OneLake, and Microsoft Graph.

Converts PDF, Word, PowerPoint, Excel, and HTML documents into Markdown, handling files up to 8 MB in a single call and routing larger or scanned files through an OCR and table-detection queue that returns Markdown plus a JSON structure file. Results arrive either by polling or a signed webhook.